About the Role We seek a hands-on Delivery Lead with 10–12 years of experience to own end-to-end execution of AI/ML projects, mentor technical teams, and collaborate with sales to scale our consulting solutions. Key Responsibilities 1. Project Delivery Own client-facing AI/ML projects from scoping to deployment, ensuring quality, timelines, and business impact. Guide teams on architecture, model design, and deployment (cloud/on-prem). 2. Team Leadership Lead and mentor data scientists/engineers, fostering skill growth and collaboration. Drive best practices in AI/ML (LLMs, MLOps, Agile). 3. Sales Collaboration Partner with sales to scope proposals, estimate efforts, and present technical solutions to clients. Must-Have Skills 10–12 years in AI/ML, with 5+ years leading teams in consulting/client delivery. Expertise in: AI/ML frameworks (TensorFlow, PyTorch, LLMs). Cloud platforms (AWS/Azure/GCP) and CI/CD pipelines. Python/R, data engineering (Spark, Kafka). Strong communication and client/stakeholder management. Good to Have Familiarity with MLOps (Docker, Kubernetes). Agile/Scrum certification. Qualifications Bachelor’s/Master’s in CS, Data Science, or related field. Certifications (e.g., AWS ML, Azure AI Engineer) are a plus. About Us Soothsayer Analytics is a global AI & Data Science consultancy headquartered in Detroit, with a thriving delivery center in Hyderabad. We design and deploy end-to-end custom Machine Learning solutions—spanning predictive analytics, optimization, NLP, and GenAI—that help leading enterprises forecast, automate, and gain a competitive edge. Join us to tackle high-impact, cross-industry projects where your ideas move rapidly from concept to production, shaping the future of data-driven decision-making. Show more Show less

Job Title: Senior Gen AI Engineer Location : Hyderabad Experience : 6–10 years Job Type : Full-time Reports To : Lead Data Scientist / Chief Scientist Job Overview We seek a Senior Gen AI Engineer with strong ML fundamentals and data engineering expertise to lead scalable AI/LLM solutions. This role focuses on integrating AI models into production, optimizing machine learning workflows, and creating scalable AI-driven systems. You will design, fine-tune, and deploy models (e.g., LLMs, RAG architectures) while ensuring robust data pipelines and MLOps practices. Key Responsibilities Agentic AI & Workflow Design : Lead design and implementation of Agentic AI systems and multi-step AI workflows. Build AI orchestration systems using frameworks like LangGraph. Utilize Agents, Tools, and Chains for complex task automation. Implement Agent-to-Agent (A2A) communication and Model Connect Protocol (MCP) for inter-model interactions. Production MLOps & Deployment : Develop, train, and deploy ML models optimized for production. Implement CI/CD pipelines (GitHub), automated testing, and robust observability (monitoring, logging, tracing) for Gen AI solutions. Containerize models (Docker) and deploy on cloud (AWS/Azure/GCP) using Kubernetes. Implement robust AI/LLM security measures and adhere to Responsible AI principles. AI Model Integration : Integrate LLMs and models from HuggingFace. Apply deep learning concepts with PyTorch or TensorFlow. Data & Prompt Engineering : Build scalable data pipelines for unstructured/text data. Design and implement embedding/chunking strategies for scalable data processing. Optimize storage/retrieval for embeddings (e.g., Pinecone, Weaviate). Utilize Prompt Engineering techniques to fine-tune AI model performance. Solution Development : Develop GenAI-driven Text-to-SQL solutions. Collaboration & Best Practices : Mentor junior team members on ML engineering best practices. Apply Agile/Scrum methodologies for project delivery. Required Skills & Qualifications Education : BS/BTech or Master's degree in Computer Science, Data Science, AI, or ML (or equivalent experience). Experience : 6+ years in ML + data engineering , with 2+ years in LLM/GenAI projects. 3+ years developing machine learning models. Technical Skills : Programming : Python. Foundation Model APIs : AzureOpenAI, OpenAI, Gemini, Anthropic, or AWS Bedrock. Agentic AI & LLM Frameworks : LangChain, LangGraph, A2A, MCP, Chains, Tools, Agents. Ability to design multi-agent systems, autonomous reasoning pipelines, and tool-calling capabilities for AI agents. MLOps/LLMOps : Docker , Kubernetes (K8s) , CI/CD , Automated Testing, Monitoring, Observability, Model Registries, Data Versioning. Cloud Platforms : AWS/Azure/GCP. Vector Databases : Pinecone, Weaviate, or similar leading platforms. Prompt Engineering . Security & Ethics : AI/LLM solution security, Responsible AI principles. Version Control : GitHub. Databases : SQL/NoSQL. Good to have : Reinforcement learning, multi-modal AI systems, complex reasoning frameworks (e.g., ReAct, Chain-of-Thought, planning algorithms). Experience in large-scale multi-agent coordination. Knowledge of deep learning frameworks such as PyTorch or TensorFlow. Experience with Feature Stores. Skills Matrix Candidates must submit a detailed resume and fill out the following matrix: Skill, Details, Skills Last Used, Experience (months), Self-Rating (0–10) Python (must) ML Engineering (must) SQL/NoSQL (must) LLM Frameworks (LangChain, LangGraph) (must) MLOps/LLMOps (Docker/K8s, CI/CD, Automated Testing, Monitoring, Observability, Model Registries, Data Versioning) (must) Cloud (AWS/Azure/GCP) (must) Vector Databases (e.g., Pinecone, Weaviate, or similar leading platforms) (must) Prompt Engineering (must) AI Agent Design (Chains, Tools) (must) A2A / MCP (highly preferred) GitHub (must) Security (AI/LLM, Responsible AI) Foundation Model APIs Reinforcement Learning Multi-modal AI systems Complex Reasoning Frameworks PyTorch / TensorFlow Feature Stores Instructions for Candidates : Provide a detailed resume highlighting projects related to LLMs, data engineering, MLOps, GenAI applications, and CI/CD with GitHub. Fill out the matrix above with accurate dates, experience duration, and self-ratings Please send your resume to jobs@SoothsayerAnalytics.com About Us: Soothsayer Analytics is a global AI & Data Science consultancy headquartered in Detroit, with a thriving delivery center in Hyderabad. We design and deploy end-to-end custom Machine Learning solutions—spanning predictive analytics, optimization, NLP, and GenAI—that help leading enterprises forecast, automate, and gain a competitive edge. Join us to tackle high-impact, cross-industry projects where your ideas move rapidly from concept to production, shaping the future of data-driven decision-making.

We seek a hands-on Delivery Lead with 1012 years of experience to own end-to-end execution of AI/ML projects, mentor technical teams, and collaborate with sales to scale our consulting solutions. Key Responsibilities 1. Project Delivery Own client-facing AI/ML projects from scoping to deployment, ensuring quality, timelines, and business impact. Guide teams on architecture, model design, and deployment (cloud/on-prem). 2. Team Leadership Lead and mentor data scientists/engineers, fostering skill growth and collaboration. Drive best practices in AI/ML (LLMs, MLOps, Agile). 3. Sales Collaboration Partner with sales to scope proposals, estimate efforts, and present technical solutions to clients. Must-Have Skills 10-12 years in AI/ML, with 5+ years leading teams in consulting/client delivery. Expertise in: o AI/ML frameworks (TensorFlow, PyTorch, LLMs). o Cloud platforms (AWS/Azure/GCP) and CI/CD pipelines. o Python/R, data engineering (Spark, Kafka). Strong communication and client/stakeholder management. Good to Have Familiarity with MLOps (Docker, Kubernetes). Agile/Scrum certification. Qualifications Bachelors/Masters in CS, Data Science, or related field. Certifications (e.g., AWS ML, Azure AI Engineer) are a plus.

We seek a Senior AI Scientist with strong ML fundamentals and data engineering expertise to lead the development of scalable AI/LLM solutions. You will design, fine-tune, and deploy models (e.g., LLMs, RAG architectures) while ensuring robust data pipelines and MLOps practices. Key Responsibilities 1. AI/LLM Development: o Fine-tune and optimize LLMs (e.g., GPT, Llama) and traditional ML models for production. o Implement retrieval-augmented generation (RAG), vector databases, and orchestration tools (e.g., LangChain). 2. Data Engineering: o Build scalable data pipelines for unstructured/text data (e.g., Spark, Kafka, Airflow). o Optimize storage/retrieval for embeddings (e.g., pgvector, Pinecone). 3. MLOps & Deployment: o Containerize models (Docker) and deploy on cloud (AWS/Azure/GCP) using Kubernetes. o Design CI/CD pipelines for LLM workflows (experiment tracking, monitoring). 4. Collaboration: o Work with DevOps to optimize latency/cost trade-offs for LLM APIs. o Mentor junior team members on ML engineering best practices. Required Skills & Qualifications Education: MS/PhD in CS/AI/Data Science (or equivalent experience). Experience: 6+ years in ML + data engineering, with 2+ years in LLM/GenAI projects.

Company : Soothsayer Analytics Working Hours : Full-Time No. of Positions : 4 Locations : Hyderabad apply now apply now Position Overview About the Role: We are seeking a talented Generative AI/LLM Engineer with a strong background in building and deploying AI models, focusing on leveraging state-of-the-art technologies like Azure OpenAI GPT-4, GPT-4 Vision, or GPT-4 Omni. Experience with Retrieval-Augmented Generation (RAG) and working with Vector Databases is essential. While fine-tuning large language models (LLMs) is a plus, it is not mandatory. A general understanding of how deep learning models are trained or fine-tuned is required. The ideal candidate should be able to quickly learn and implement advanced techniques, even if they do not initially possess all the required experience. Key Responsibilities Design, develop, and deploy generative AI models using GPT-4 variants, including GPT-4 Vision and GPT-4 Turbo, tailored to address specific business needs. Implement and optimize Retrieval-Augmented Generation (RAG) techniques for enhanced data-driven solutions. Build and manage AI services using Python frameworks such as LangChain or LlamaIndex, and develop APIs with FastAPI or Quart for efficient integration. Focus on scalability, performance, and optimization of AI solutions across cloud environments, particularly with Azure and AWS. Work with Vector Databases (mandatory) and optionally Graph Databases for enhanced data management. Utilize Cosmos DB and SQL for robust data storage and management solutions. Apply MLOps or LLMOps practices to automate and streamline the AI model lifecycle, including CI/CD pipelines, monitoring, and maintenance. Implement and manage Azure Pipelines for continuous integration and deployment. Continuously research and adopt the latest advancements in AI, with a focus on quick learning and implementation of emerging technologies. Required Skills And Qualifications Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field. A minimum of 1+ years of experience specifically in Generative AI/LLM technologies, and 5+ years of experience in related fields. Proficiency in Python and experience with frameworks like LangChain, LlamaIndex, FastAPI, or Quart. Expertise in Retrieval-Augmented Generation (RAG) and experience with Vector Databases (mandatory). Experience with Cosmos DB and SQL. Fine-tuning LLMs and experience with Graph Databases are good to have but not mandatory. Proven experience in MLOps, LLMOps, or DevOps with a strong understanding of CI/CD processes, automation, and pipeline management. Familiarity with containers, Docker, or Kubernetes is a plus. Familiarity with cloud platforms, particularly Azure or AWS, and experience with cloud-native AI services. Strong problem-solving abilities and a proactive approach to learning new AI trends and best practices quickly.

Working Hours : Full Time Locations : India (Remote) Experience : 5 years apply now apply now About The Role Work with team members to help respond/ creation of Statement of Work (SOWs), Request for Proposals (RFPs), Request for Quotations (RFQs), Requests for Information (RFIs), and manage the proposal development process to ensure on-time delivery of compelling, compliant, and well-written proposals. Exhibit strong writing skills, excellent attention to detail, thrive in a fast-past environment, be able to track multiple ongoing projects and responsibilities simultaneously. Self-starter, multitask-er who works well under pressure, and follows through on tasks. Maintain, augment, and improve the library of reusable components, templates, and processes to reduce response time and improve quality on future proposals. Assist with management of proposal deadlines by establishing priorities and target dates for information gathering, writing, review, and approval; entering and monitoring tracking data; coordinating requirements with contributors; contributing proposal status information to review meetings; transmitting proposals. Assist with developing & preparing proposals by assembling information including project nature, objectives/value proposition/deliverables, implementation, methods, timetable, and evaluation; writing, revising, and editing drafts including executive summaries, conclusions, and organization credentials. Obtain approvals by reviewing proposals with key team members and project managers as required. Improve proposal-writing results by evaluating and re-designing processes, approach, coordination, and boilerplate; implementing changes. Direct proposal kickoff and debrief meetings, for hand-off to project managers. Follow up on unsuccessful proposals to develop recommendations for improving the success rate. Coordinate delivery of the document to ensure submission deadlines are met. Technical Writer Develop materials / contents for websites, case studies, technical documentation, speaking engagements, workshops, Social media posts, and/or webinars. Study solutions and talk with the solution implementation team to create content for the solution. Incorporate animation, graphs, illustrations, or photographs to increase users’ understanding of the material. Select appropriate media, such as manuals or videos, for message or audience. Create digital operating instructions, how-to manuals, assembly instructions, and frequently asked questions. Key Skills Word, Powerpoint, Exel, Data Science Education & Experience Bachelor’s degree in a related field. 5+ years of experience in technical writing. 5+ years of experience in proposal writing. Experience writing proposals and/or knowledge of Data Science (AI, ML) is a big plus. Excellent communication skills, both verbal and written. Extensive experience reading and analyzing RFP requirements; ability to effectively identify and develop proposal. Proven experience working independently to produce draft materials under tight deadlines. Capable of setting and meeting deadlines. Ability to work well in both independent and highly collaborative settings. Ability to manage multiple writing projects concurrently. Must be adept at independent research to support written deliverables.

We seek a Senior Gen AI Engineer with strong ML fundamentals and data engineering expertise to lead scalable AI/LLM solutions. This role focuses on integrating AI models into production, optimizing machine learning workflows, and creating scalable AI-driven systems. You will design, fine-tune, and deploy models (e.g., LLMs, RAG architectures) while ensuring robust data pipelines and MLOps practices. Key Responsibilities Agentic AI & Workflow Design: Lead design and implementation of Agentic AI systems and multi-step AI workflows. Build AI orchestration systems using frameworks like LangGraph. Utilize Agents, Tools, and Chains for complex task automation. Implement Agent-to-Agent (A2A) communication and Model Connect Protocol (MCP) for inter-model interactions. Production MLOps & Deployment: Develop, train, and deploy ML models optimized for production. Implement CI/CD pipelines (GitHub), automated testing, and robust observability (monitoring, logging, tracing) for Gen AI solutions. Containerize models (Docker) and deploy on cloud (AWS / Azure/ GCP) using Kubernetes. Implement robust AI/LLM security measures and adhere to Responsible AI principles. AI Model Integration: Integrate LLMs and models from HuggingFace. Apply deep learning concepts with PyTorch or TensorFlow. Data & Prompt Engineering: Build scalable data pipelines for unstructured/text data. Design and implement embedding/chunking strategies for scalable data processing. Optimize storage/retrieval for embeddings (e.g., Pinecone, Weaviate). Utilize Prompt Engineering techniques to fine-tune AI model performance. Solution Development: Develop GenAI-driven Text-to-SQL solutions. Programming: Python. Foundation Model APIs: AzureOpenAI, OpenAI, Gemini, Anthropic, or AWS Bedrock. Agentic AI & LLM Frameworks: LangChain, LangGraph, A2A, MCP, Chains, Tools, Agents. Ability to design multi-agent systems, autonomous reasoning pipelines, and tool-calling capabilities for AI agents. MLOps/LLMOps: Docker , Kubernetes (K8s) , CI/CD , Automated Testing, Monitoring, Observability, Model Registries, Data Versioning. Cloud Platforms: AWS/Azure/GCP. Vector Databases: Pinecone, Weaviate, or similar leading platforms. Prompt Engineering. Security & Ethics: AI/LLM solution security, Responsible AI principles. Version Control: GitHub. Databases: SQL/NoSQL.

We seek a Senior Full Stack AI Engineer passionate about rapidly developing and demonstrating Agentic AI and workflow solutions. This role focuses on quickly translating innovative ideas into tangible Proofs of Concept (POCs), leveraging full-stack capabilities to build attractive user interfaces, integrate sophisticated AI agents, and deploy working solutions for impactful demonstrations. Key Responsibilities Rapid Agentic AI POC Development: Lead agile development of end-to-end Agentic AI and complex workflow POCs from concept to demonstration, ensuring rapid iteration and delivery. Design and implement multi-turn conversational Agents, Tools, and Chains. Full Stack Application Development: Develop attractive and intuitive front-end user interfaces (e.g., React, Next.js) and robust back-end APIs (e.g., FastAPI, Flask). Implement comprehensive testing strategies across the full stack. AI Orchestration & Integration: Utilize frameworks like Langgraph (or equivalents such as CrewAI, AutoGen) to orchestrate complex AI agent systems and multi-step workflows. Implement Agent-to-Agent (A2A) communication and adhere to Model Connect Protocol (MCP) for inter-model interactions. Apply advanced prompt engineering techniques. Deployment & Demonstration: Containerize applications (Docker) and deploy on Kubernetes for scalable POCs. Establish and utilize CI/CD pipelines for continuous integration and delivery. Prepare and deliver compelling technical demonstrations. Experience: 6+ years in ML + data engineering, with 2+ years in LLM/GenAI projects. Proven rapid prototyping track record. Technical Skills: Programming: Python, JavaScript/TypeScript (React, Next.js). AI/ML Fundamentals: LLMs, prompt engineering, Agentic AI architectures. Agentic AI & LLM Frameworks: Langgraph, CrewAI, AutoGen, A2A, MCP, Chains, Tools, Agents. Front-end: React, Next.js. Back-end: FastAPI, Flask. Databases: Vector databases (Pinecone, Weaviate), SQL/NoSQL. DevOps: Docker, Kubernetes (K8s), CI/CD, Testing. Cloud Platforms: AWS/Azure/GCP. Good to have: Experience with cloud-native AI/ML services (e.g., AWS SageMaker, Azure ML, GCP Vertex AI). Familiarity with UI/UX design principles for creating engaging interfaces. Experience with asynchronous programming patterns in Python. Knowledge of caching mechanisms (e.g., Redis) for optimizing application performance. Understanding of general Machine Learning concepts and common algorithms beyond LLMs.

You will be working as a Mid-Level Full Stack Developer at Soothsayer Analytics in Hyderabad. Your main responsibility will be to contribute to the development of Generative AI applications using Azure and OpenAI technologies. This role requires you to work on both front-end and back-end components of AI applications, leveraging React and Python, and integrating Azure OpenAI models, Bing Search, and Azure ML Studio into custom-built applications. Your key responsibilities include developing and maintaining front-end and back-end components of AI applications, integrating Azure OpenAI models and Azure services, working with databases such as Cosmos DB, SQL Server, and Weaviate, developing secure and scalable applications using VNet and Private Endpoint configurations, implementing APIs for interaction with large language models and document processing systems, collaborating with AI engineers to design and deploy Generative AI solutions, and implementing CI/CD automation using Azure DevOps and GitHub. To be successful in this role, you should have 3+ years of professional experience in full-stack development, strong proficiency in front-end development using React and back-end development with Python, experience with Azure services, familiarity with integrating AI models, experience with cloud security practices, knowledge of containerization and orchestration, familiarity with CI/CD pipelines and version control, and ideally, experience with Weaviate, LangChain, Hugging Face, or Neo4j databases. If you are passionate about developing innovative AI applications and have the required skills and experience, we encourage you to apply for this exciting opportunity at Soothsayer Analytics.,