Join us and contribute to the discovery of medicines that will impact lives! Hyderabad, India | Hybrid | Full-Time About Aganitha High-throughput experimentation, computational & data-driven modeling, and the advent of the Open Science era are fundamentally transforming research, discovery, and development across diverse industries. Aganitha is at the forefront of co-innovation with global clients, shaping next-generation R&D (aganitha.ai). While our primary client base has been in global Biopharma, we are actively expanding our collaborations into consumer brands and, in the near future, the materials design industry. As a Scientist at Aganitha, you will be instrumental in leveraging cutting-edge advances in computational chemistry, materials science, soft matter physics, AI/ML, and high-performance computing in the Cloud. You will contribute to accelerating design and development across a spectrum of applications, including but not limited to: small molecule therapeutics, biologics, gene, cell & RNA therapies within Biopharma; new product formulations for consumer brands; and novel materials for various industrial applications. You will collaborate closely with research leaders at our client organizations, identifying their needs and designing innovative solutions. Working with our internal technical and scientific teams, you will drive solutions from concept to launch and growth. You may also interact with external vendors to coordinate experimental validation of the in silico solutions developed at Aganitha. To excel in this role, you must possess a strong interest in engaging with customers to apply the latest scientific and technological advancements for R&D acceleration, thereby contributing to Aganitha’s growth. Key Responsibilities Perform advanced computational simulations (e.g., Periodic and non-periodic Quantum Mechanics, Atomistic and/or Coarse-grained variants of Molecular Dynamics, Monte Carlo, Brownian Dynamics, Langevin Dynamics, Dissipative Particle Dynamics, etc.) to understand stability, complex interactions and design principles relevant to various hard and soft matter systems e.g., inorganic/organic crystalline materials, surfactants, polymers, colloids, biomolecules, etc. Apply computational methods to materials design for various applications such as semiconductor devices, capture and storage of greenhouse gases, skin and body care formulations, excipients, etc. Conduct molecular modeling studies to investigate self-assembly phenomena and interactions between various components in the formulation of a material, such as surfactant or polymer interactions with diverse substrates (e.g., skin, hair, fabric). Interpret results from domain-specific simulations (e.g., MD, DFT) and structure the scientific data into features or descriptors—such as radial distribution functions, binding energies, surface areas, or density profiles—relevant for downstream AI/ML modeling of material properties or formulation performance. Understand, analyze, critique, and implement research papers, tailoring approaches to specific problem contexts. Develop clear and concise narratives of data-driven analyses performed using computational techniques. Effectively articulate and communicate complex domain knowledge to cross-functional teams. Participate actively in requirements gathering, design discussions, and demonstrations. Continuously learn and stay up-to-date on emerging technologies and scientific advancements in computational chemistry, materials science, and related fields—research opportunities for applying advanced computational methods to evolving industry challenges. Educational & Research Qualifications PhD, post-doctoral research, or equivalent higher studies in Computational Chemistry or Computational Physics applied to Materials Science, Polymer Science, Surfactant Science, Colloidal Chemistry, Soft Matter Physics, Fluid Dynamics, or a closely related field. Demonstrated first-hand research experience in problems in the domain of materials science, for example: Materials design for various applications such as semi-conductor devices, capture and storage of green-house gases, skin and body care formulations, excipients. Crystal structure prediction of inorganic/organic molecules Molecular/colloidal self-assembly and crystallization phenomena Interactions between various components in the formulation of a material, e.g., surfactant or polymer interactions with diverse substrates (e.g., skin, hair, fabric). Proficiency in at least one of the advanced computational chemistry methods viz. periodic and non-periodic Quantum Mechanics, Atomistic and/or Coarse-grained variants of Molecular Dynamics, Monte Carlo, Brownian Dynamics, Langevin Dynamics, Dissipative Particle Dynamics. Technical Skills Familiarity with computational chemistry packages such as Quantum Espresso, VASP, LAMMPS, PySCF, GROMACS, NAMD, CP2K, SIESTA, OpenMM, or similar. Must have a keen understanding of the interface of computer technology, high-throughput sciences, and chemistry/materials science. Added Advantages Familiarity with AI/ML methods and their application in scientific research. Expertise in computer programming (e.g., Python, C++, Fortran). Exposure to High-Performance Computing (HPC) environments and parallel computing. Soft Skills Excellent verbal and written communication skills are essential. Excellent communication skills, with the ability to distill complex scientific concepts into easily understandable insights for diverse audiences. Right attitude to collaborate effectively within a cross-functional team environment. Ability to quickly grasp new scientific domains and apply critical thinking to novel challenges. Comfortable working in a fast-paced, rapidly changing environment. Strong interest and aptitude to break down large, complex problem statements into manageable work packets.

Join us and contribute to the discovery of medicines that will impact lives! Hyderabad, India | Hybrid | Full-Time About Aganitha High-throughput experimentation, computational & data-driven modeling, and the advent of the Open Science era are fundamentally transforming research, discovery, and development across diverse industries. Aganitha is at the forefront of co-innovation with global clients, shaping next-generation R&D (aganitha.ai). While our primary client base has been in global Biopharma, we are actively expanding our collaborations into consumer brands and, in the near future, the materials design industry. As a Scientist at Aganitha, you will be instrumental in leveraging cutting-edge advances in computational chemistry, materials science, soft matter physics, AI/ML, and high-performance computing in the Cloud. You will contribute to accelerating design and development across a spectrum of applications, including but not limited to: small molecule therapeutics, biologics, gene, cell & RNA therapies within Biopharma; new product formulations for consumer brands; and novel materials for various industrial applications. You will collaborate closely with research leaders at our client organizations, identifying their needs and designing innovative solutions. Working with our internal technical and scientific teams, you will drive solutions from concept to launch and growth. You may also interact with external vendors to coordinate experimental validation of the in silico solutions developed at Aganitha. To excel in this role, you must possess a strong interest in engaging with customers to apply the latest scientific and technological advancements for R&D acceleration, thereby contributing to Aganitha’s growth. Key Responsibilities Perform Molecular Dynamics (MD) simulations and Quantum Mechanics (QM) calculations to deeply understand biomolecular interactions (protein-ligand, lipid-protein, lipid-nucleic acid interactions, etc.), support small molecule or PROTAC design, facilitate catalyst design for chemical reactions, investigate complex chemical reaction mechanisms, and conduct polymorph screening. Define appropriate data models and identify relevant features for developing AI/ML-based models for predicting crucial properties such as ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) profiles, lattice energies, reaction yields, and selectivity. Understand, analyze, critique, and implement cutting-edge research, effectively tailoring the approaches to specific problem contexts. Develop clear, concise, and compelling narratives of data-driven analyses performed using QM or MD techniques, making complex findings accessible. Effectively articulate and communicate intricate domain knowledge to a cross-functional team. Actively participate in requirements gathering, design discussions, and solution demonstrations. Continuously learn and stay up-to-date on emerging technologies and scientific advancements in computational chemistry and structural biology. Research opportunities for the application of AI in the development of emerging therapeutic techniques. Qualifications PhD in Computational Chemistry, Cheminformatics, Structural Biology, Biochemistry, Biophysics, or a closely related field, coupled with a genuine passion for continuous learning. Strong interest in computational and data-driven methods with a clear understanding of how in silico approaches can significantly accelerate drug discovery and development processes. Must possess a keen understanding of the interface of computer technology, high-throughput sciences, and chemistry/biology. Demonstrated experience with computational tools and techniques commonly used in structural biology and biomolecular modeling (e.g., protein-ligand docking, protein-protein interaction studies, homology modeling). Prior experience in the Biopharma industry is a plus. Desired Technical Skills/Expertise Hands-on experience with molecular dynamics software packages (e.g., GROMACS, NAMD, AMBER, CHARMM,OpenMM, etc.). Familiarity with quantum chemistry software (e.g., PySCF, ORCA, NWChem, Quantum Espresso, etc.). Proficiency in at least one scripting/programming language, preferably Python, for data analysis, automation, and workflow development. Understanding of biomolecular docking and virtual screening methodologies. Exposure to data visualization tools for scientific data. Added Advantages Familiarity with AI/ML methods and their application in scientific research, including areas like QSAR/QSPR, generative models for molecular design, or predictive analytics in drug discovery. Expertise in computer programming (e.g., Python, C++, Fortran), including developing robust and reproducible code. Exposure to High-Performance Computing (HPC) environments, cloud computing platforms, and parallel computing techniques. Experience with database management in a scientific context. Soft Skills Excellent verbal and written communication skills are essential, with the ability to clearly articulate complex scientific and computational concepts to both technical and non-technical audiences. A proactive and collaborative attitude to work effectively within cross-functional teams, fostering an environment of shared learning and problem-solving. Demonstrated ability to quickly grasp new scientific domains and apply critical thinking to novel challenges, adapting to evolving project needs. Strong problem-solving mindset, capable of independently identifying issues and proposing effective solutions. Proven interest and aptitude to break down large, complex problem statements into manageable and actionable work packets. Comfortable working effectively in a fast-paced, rapidly changing research and development environment.

Join us and contribute to the discovery of medicines that will impact lives! Hyderabad, India | Hybrid | Full-Time About Aganitha High-throughput experimentation, computational & data-driven modeling, and the advent of the Open Science era are fundamentally transforming research, discovery, and development across diverse industries. Aganitha is at the forefront of co-innovation with global clients, shaping next-generation R&D (aganitha.ai). While our primary client base has been in global Biopharma, we are actively expanding our collaborations into consumer brands and, in the near future, the materials design industry. As a Scientist at Aganitha, you will be instrumental in leveraging cutting-edge advances in computational chemistry, materials science, soft matter physics, AI/ML, and high-performance computing in the Cloud. You will contribute to accelerating design and development across a spectrum of applications, including but not limited to: small molecule therapeutics, biologics, gene, cell & RNA therapies within Biopharma; new product formulations for consumer brands; and novel materials for various industrial applications. You will collaborate closely with research leaders at our client organizations, identifying their needs and designing innovative solutions. Working with our internal technical and scientific teams, you will drive solutions from concept to launch and growth. You may also interact with external vendors to coordinate experimental validation of the in silico solutions developed at Aganitha. To excel in this role, you must possess a strong interest in engaging with customers to apply the latest scientific and technological advancements for R&D acceleration, thereby contributing to Aganitha’s growth. Key Responsibilities Design and develop AI/ML models to solve complex problems in computational chemistry, such as predicting molecular properties, material behaviors, or reaction outcomes. Curate, process, and analyze scientific datasets from various sources, including literature and experimental data, ensuring data quality and readiness for model training. Develop intelligent featurization strategies that accurately represent chemical structures, physical properties, or biological interactions, drawing upon your scientific understanding. Implement, train, and evaluate cutting-edge Machine Learning and Deep Learning algorithms (e.g., CNNs, RNNs, LSTMs, Transformer architectures) to build robust predictive models. Rigorously validate models against client-provided data and established benchmarks, ensuring their accuracy, generalizability, and utility. Translate complex technical and scientific findings into clear, actionable insights for both technical and non-technical stakeholders. Collaborate effectively with computational chemists, data scientists, and wet lab scientists to define project requirements, iterate on solutions, and ensure successful deployment. Stay abreast of the latest advancements in AI/ML, computational chemistry, and relevant scientific domains, continuously seeking opportunities to apply new methodologies. Qualifications PhD, post-doctoral research, or equivalent higher studies in Computational Chemistry, Cheminformatics, Materials Science, Chemical Engineering, Biochemistry, or a closely related scientific discipline. Strong foundational understanding of the scientific principles underlying computational chemistry, materials science, or related fields (e.g., colloidal chemistry, polymer science, surfactant chemistry, soft condensed matter physics, etc.). Solid mathematical intuition of Machine Learning algorithms, including Deep Learning architectures such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), LSTMs, and Transformer architectures. Proficiency in modular, typed, and object-oriented Python programming. A high-level understanding of the ML/DL project lifecycle , from data preparation and feature engineering through model development, training, evaluation, and deployment. Excellent problem-solving skills and the ability to apply critical thinking to complex scientific and technical challenges. Strong verbal and written communication skills , with the ability to effectively communicate technical concepts to diverse audiences. Desired Technical Skills/Expertise Hands-on experience with molecular dynamics software packages (e.g., GROMACS, NAMD, AMBER, CHARMM,OpenMM, etc.). Familiarity with quantum chemistry software (e.g., PySCF, ORCA, NWChem, Quantum Espresso, etc.). Proficiency in at least one scripting/programming language, preferably Python, for data analysis, automation, and workflow development. Understanding of biomolecular docking and virtual screening methodologies. Exposure to data visualization tools for scientific data. Added Advantages Experience in effectively building and deploying ML solutions using popular frameworks such as PyTorch, TensorFlow, Keras, or scikit-learn. Proficiency in shell scripting. Big Plus Exposure to large language models (LLMs) such as ChatGPT, Claude, or Gemini, and practical experience in utilizing such tools for day-to-day work (e.g., writing research reports, understanding new concepts, generating code).

Join us and contribute to the discovery of medicines that will impact lives! Hyderabad, India | Hybrid | Full-Time About Aganitha High-throughput experimentation, computational & data-driven modeling, and the advent of the Open Science era are fundamentally transforming research, discovery, and development across diverse industries. Aganitha is at the forefront of co-innovation with global clients, shaping next-generation R&D (aganitha.ai). While our primary client base has been in global Biopharma, we are actively expanding our collaborations into consumer brands and, in the near future, the materials design industry. As a Scientist at Aganitha, you will be instrumental in leveraging cutting-edge advances in computational chemistry, materials science, soft matter physics, AI/ML, and high-performance computing in the Cloud. You will contribute to accelerating design and development across a spectrum of applications, including but not limited to: small molecule therapeutics, biologics, gene, cell & RNA therapies within Biopharma; new product formulations for consumer brands; and novel materials for various industrial applications. You will collaborate closely with research leaders at our client organizations, identifying their needs and designing innovative solutions. Working with our internal technical and scientific teams, you will drive solutions from concept to launch and growth. You may also interact with external vendors to coordinate experimental validation of the in silico solutions developed at Aganitha. To excel in this role, you must possess a strong interest in engaging with customers to apply the latest scientific and technological advancements for R&D acceleration, thereby contributing to Aganitha’s growth. Key Responsibilities Perform advanced computational simulations (e.g., Periodic and non-periodic Quantum Mechanics, Atomistic and/or Coarse-grained variants of Molecular Dynamics, Monte Carlo, Brownian Dynamics, Langevin Dynamics, Dissipative Particle Dynamics, etc.) to understand stability, complex interactions and design principles relevant to various hard and soft matter systems e.g., inorganic/organic crystalline materials, surfactants, polymers, colloids, biomolecules, etc. Apply computational methods to materials design for various applications such as semiconductor devices, capture and storage of greenhouse gases, skin and body care formulations, excipients, etc. Conduct molecular modeling studies to investigate self-assembly phenomena and interactions between various components in the formulation of a material, such as surfactant or polymer interactions with diverse substrates (e.g., skin, hair, fabric). Interpret results from domain-specific simulations (e.g., MD, DFT) and structure the scientific data into features or descriptors—such as radial distribution functions, binding energies, surface areas, or density profiles—relevant for downstream AI/ML modeling of material properties or formulation performance. Understand, analyze, critique, and implement research papers, tailoring approaches to specific problem contexts. Develop clear and concise narratives of data-driven analyses performed using computational techniques. Effectively articulate and communicate complex domain knowledge to cross-functional teams. Participate actively in requirements gathering, design discussions, and demonstrations. Continuously learn and stay up-to-date on emerging technologies and scientific advancements in computational chemistry, materials science, and related fields—research opportunities for applying advanced computational methods to evolving industry challenges. Educational & Research Qualifications PhD, post-doctoral research, or equivalent higher studies in Computational Chemistry or Computational Physics applied to Materials Science, Polymer Science, Surfactant Science, Colloidal Chemistry, Soft Matter Physics, Fluid Dynamics, or a closely related field. Demonstrated first-hand research experience in problems in the domain of materials science, for example: Materials design for various applications such as semi-conductor devices, capture and storage of green-house gases, skin and body care formulations, excipients. Crystal structure prediction of inorganic/organic molecules Molecular/colloidal self-assembly and crystallization phenomena Interactions between various components in the formulation of a material, e.g., surfactant or polymer interactions with diverse substrates (e.g., skin, hair, fabric). Proficiency in at least one of the advanced computational chemistry methods viz. periodic and non-periodic Quantum Mechanics, Atomistic and/or Coarse-grained variants of Molecular Dynamics, Monte Carlo, Brownian Dynamics, Langevin Dynamics, Dissipative Particle Dynamics. Technical Skills Familiarity with computational chemistry packages such as Quantum Espresso, VASP, LAMMPS, PySCF, GROMACS, NAMD, CP2K, SIESTA, OpenMM, or similar. Must have a keen understanding of the interface of computer technology, high-throughput sciences, and chemistry/materials science. Added Advantages Familiarity with AI/ML methods and their application in scientific research. Expertise in computer programming (e.g., Python, C++, Fortran). Exposure to High-Performance Computing (HPC) environments and parallel computing. Soft Skills Excellent verbal and written communication skills are essential. Excellent communication skills, with the ability to distill complex scientific concepts into easily understandable insights for diverse audiences. Right attitude to collaborate effectively within a cross-functional team environment. Ability to quickly grasp new scientific domains and apply critical thinking to novel challenges. Comfortable working in a fast-paced, rapidly changing environment. Strong interest and aptitude to break down large, complex problem statements into manageable work packets.

Join us and contribute to the discovery of medicines that will impact lives! Hyderabad, India | Hybrid | Full-Time About Aganitha High-throughput experimentation, computational & data-driven modeling, and the advent of the Open Science era are fundamentally transforming research, discovery, and development across diverse industries. Aganitha is at the forefront of co-innovation with global clients, shaping next-generation R&D (aganitha.ai). While our primary client base has been in global Biopharma, we are actively expanding our collaborations into consumer brands and, in the near future, the materials design industry. As a Scientist at Aganitha, you will be instrumental in leveraging cutting-edge advances in computational chemistry, materials science, soft matter physics, AI/ML, and high-performance computing in the Cloud. You will contribute to accelerating design and development across a spectrum of applications, including but not limited to: small molecule therapeutics, biologics, gene, cell & RNA therapies within Biopharma; new product formulations for consumer brands; and novel materials for various industrial applications. You will collaborate closely with research leaders at our client organizations, identifying their needs and designing innovative solutions. Working with our internal technical and scientific teams, you will drive solutions from concept to launch and growth. You may also interact with external vendors to coordinate experimental validation of the in silico solutions developed at Aganitha. To excel in this role, you must possess a strong interest in engaging with customers to apply the latest scientific and technological advancements for R&D acceleration, thereby contributing to Aganitha’s growth. Key Responsibilities Design and develop AI/ML models to solve complex problems in computational chemistry, such as predicting molecular properties, material behaviors, or reaction outcomes. Curate, process, and analyze scientific datasets from various sources, including literature and experimental data, ensuring data quality and readiness for model training. Develop intelligent featurization strategies that accurately represent chemical structures, physical properties, or biological interactions, drawing upon your scientific understanding. Implement, train, and evaluate cutting-edge Machine Learning and Deep Learning algorithms (e.g., CNNs, RNNs, LSTMs, Transformer architectures) to build robust predictive models. Rigorously validate models against client-provided data and established benchmarks, ensuring their accuracy, generalizability, and utility. Translate complex technical and scientific findings into clear, actionable insights for both technical and non-technical stakeholders. Collaborate effectively with computational chemists, data scientists, and wet lab scientists to define project requirements, iterate on solutions, and ensure successful deployment. Stay abreast of the latest advancements in AI/ML, computational chemistry, and relevant scientific domains, continuously seeking opportunities to apply new methodologies. Qualifications PhD, post-doctoral research, or equivalent higher studies in Computational Chemistry, Cheminformatics, Materials Science, Chemical Engineering, Biochemistry, or a closely related scientific discipline. Strong foundational understanding of the scientific principles underlying computational chemistry, materials science, or related fields (e.g., colloidal chemistry, polymer science, surfactant chemistry, soft condensed matter physics, etc.). Solid mathematical intuition of Machine Learning algorithms, including Deep Learning architectures such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), LSTMs, and Transformer architectures. Proficiency in modular, typed, and object-oriented Python programming. A high-level understanding of the ML/DL project lifecycle , from data preparation and feature engineering through model development, training, evaluation, and deployment. Excellent problem-solving skills and the ability to apply critical thinking to complex scientific and technical challenges. Strong verbal and written communication skills , with the ability to effectively communicate technical concepts to diverse audiences. Desired Technical Skills/Expertise Hands-on experience with molecular dynamics software packages (e.g., GROMACS, NAMD, AMBER, CHARMM,OpenMM, etc.). Familiarity with quantum chemistry software (e.g., PySCF, ORCA, NWChem, Quantum Espresso, etc.). Proficiency in at least one scripting/programming language, preferably Python, for data analysis, automation, and workflow development. Understanding of biomolecular docking and virtual screening methodologies. Exposure to data visualization tools for scientific data. Added Advantages Experience in effectively building and deploying ML solutions using popular frameworks such as PyTorch, TensorFlow, Keras, or scikit-learn. Proficiency in shell scripting. Big Plus Exposure to large language models (LLMs) such as ChatGPT, Claude, or Gemini, and practical experience in utilizing such tools for day-to-day work (e.g., writing research reports, understanding new concepts, generating code).

Join our team and contribute to the discovery of medicines that will impact lives! Located in Hyderabad, India, Aganitha is dedicated to accelerating drug discovery and development for Biopharma and Biotech R&D through innovative in silico solutions. Our team leverages Computational Biology & Chemistry, High throughput Sciences, AI, ML, HPC, Cloud, Data, and DevOps to drive advancements in the industry. In silico solutions have revolutionized the biopharma and biotech sectors, and our team of experts is at the forefront of this transformation. We are constantly expanding our multi-disciplinary team in Genomics, AI, and Cloud computing to accelerate drug discovery and development. Our passion lies in working in an innovation-rich, research-powered startup that bridges various disciplines to bring medicines to market faster. Collaborating with innovative Biopharma companies globally, we are committed to pushing boundaries and making a difference. As a part of our team, your key responsibilities will include engaging and co-innovating with R&D teams of our Biopharma clients, leading architecture initiatives, designing and overseeing implementation of solutions for BioPharma R&D, managing Engineering teams, enhancing reuse with platforms and frameworks, collaborating with business users, driving scope definition, and ensuring delivered solutions meet technical and functional requirements. Desired skills and expertise for this position include experience in big data engineering, cloud and DevOps automation, application development with modern tech stacks, and proficiency in Machine Learning and AI. Excellent communication skills and the ability to work in multidisciplinary teams are also essential. We are seeking individuals with educational qualifications such as a Bachelors, Masters, or Ph.D. in Computer Science or a related technical field to join our dynamic team at Aganitha. If you are passionate about making a difference in drug discovery and development, we invite you to join us in our mission to bring out your best and be limitless!,

Join us and contribute to the discovery of medicines that will impact lives! Aganitha is accelerating drug discovery and development for Biopharma and Biotech R&D with in silico solutions leveraging Computational Biology & Chemistry, High throughput Sciences, AI, ML, HPC, Cloud, Data, and DevOps. In silico solutions are transforming the biopharma and biotech industries. Our cross-domain science and technology team of experts embark upon and industrialize this transformation. We continually expand our world-class multi-disciplinary team in Genomics, AI, and Cloud computing, accelerating drug discovery and development. What drives us is the joy of working in an innovation-rich, research-powered startup bridging multiple disciplines to bring medicines faster for human use. We are working with several innovative Biopharma companies and expanding our client base globally. Read about how and what solutions we build. Aganitha, which means countless or limitless in Sanskrit, serves as a reminder and inspiration about the limitless potential in each one of us. Come join us to bring out your best and be limitless! Key Responsibilities: - Engage and co-innovate with R&D teams of our Biopharma clients, and collaborate with a team of Biologists, Medicinal Chemists, Computational Chemists, Computational Biologists, Data Scientists, Data Engineers, and Web Developers to create the next generation of innovative computational solutions for drug discovery and development. - Lead architecture initiatives from inception to completion - Design and oversee implementation of solutions for BioPharma R&D - Manage Engineering teams using Agile methodologies - Enhance reuse with platforms, frameworks, and libraries - Collaborate with business users to create architecture in alignment with a business need - Drive scope definition, requirements analysis, functional and technical design, application build, product configuration, unit testing, and production deployment and ensure delivered solutions meet/perform to technical and functional/non-functional requirements. - Champion the adoption of reusable architecture assets to improve efficiency - Produce documentation to aid in the understanding of existing architecture solutions - Advise our technical teams to optimize the recommended product suite in defining, building, and deploying end-to-end solutions - Lead the translation of the clients business requirements into systems design - Drive the development of prototypes and technology demonstrators within microservice architecture, cloud-native solutions - Design and document system installation and upgrade guides, specifications, and related standards and guide technical team, application specialists - Design application user guides, document common workflows, prepare training materials and conduct or participate in knowledge-sharing sessions with technical teams - Design future state reference architectures that will provide a template for teams to achieve security, scalability, reliability, and maintainability - Design and implement optimal deployment strategies and custom interfaces for integration with customer systems and technologies - Help customers tackle thorny technical issues by collaborating to create smart, efficient, and effective solutions - Work closely with customers on the installation, configuration, and update/maintenance of on-premises or cloud-hosted installations of our scientific computing and enterprise software applications - Collaborate with product managers, developers, and scientists, to improve the deployment, support, and configuration of our applications Desired Skills / Expertise: - Big data engineering with distributed computing frameworks - Cloud and DevOps automation - App dev with modern tech stacks of Python, ReactJS, and fit-for-purpose database technologies - Experience in directing/building solutions leveraging Machine learning (ML) and AI (Deep learning) - Excellent communication skills with a desire to work in multidisciplinary teams Educational Qualifications: - Bachelors / Masters / Ph.D. in Computer Science or related technical field,