We are seeking an experienced Adobe Workfront Developer with expertise in Workfront and Workfront Fusion to design, implement, and optimise work management and automation solutions. The ideal candidate will have a strong technical and functional understanding of Adobe Workfront, extensive experience with workflow automation, and the ability to mentor teams while driving system efficiency. Role Expectations : - Design, develop, and maintain workflow automation using Adobe Workfront and Workfront Fusion. - Configure Workfront objects, including custom forms, templates, approval workflows, access levels, and layout templates to optimize user experience. - Automate business processes and optimize workflow performance using Workfront Fusion and APIs. - Integrate Adobe Workfront with Adobe Experience Manager (AEM), Adobe Assets, and other third-party applications. - Develop and maintain Workfront Fusion automation workflows to streamline processes. - Ensure seamless data flow between Workfront and other enterprise tools using native connectors and APIs. - Configure Workfront features, such as custom forms, templates, approval workflows, and advanced reporting (text mode). - Develop and maintain integrations using Workfront Fusion with AEM, Adobe Assets, and other enterprise tools. Must Have : - Deep knowledge of Adobe Workfront, including setup, object types, and reporting. - Experience with Workfront Fusion and workflow automation. - Strong understanding of integration processes with AEM and other enterprise tools. - Strong troubleshooting skills for resolving Workfront and Fusion-related issues. Nice to Have : - Familiarity with advanced reporting (text mode) in Workfront. - Experience with system governance and managing user access levels. Experience : - 1+ years of Workfront implementation experience for large organisations. - 1+ years of experience with Workfront Fusion integration. - Hands-on experience with Workfront setup, workflows, and reporting dashboards. Certifications : - Adobe Workfront Developer Core & Fusion Certifications. - A bachelor's degree in Computer Science, Engineering, Information Technology, or a related field is preferred.

Key Responsibilities : - Integration of user-facing elements developed by front-end developers. - Build efficient, testable, and reusable PHP modules. - Solve complex performance problems and architectural challenges. - Integration of data storage solutions. Skills And qualifications : - Strong knowledge of PHP web frameworks {such as Laravel, database management. - Understanding the fully synchronous behavior of PH. - Understanding of MVC design pattern. - Basic understanding of front-end technologies, such as JavaScript, HTML5, and CSS. - Knowledge of object-oriented PHP programming. - Understanding accessibility and security compliance. - Strong knowledge of the common PHP or web server exploits and their solution. - Understanding fundamental design principles behind a scalable application. - User authentication and authorization between multiple systems, servers, and environment. - Integration of multiple data sources and databases into one system. - Familiarity with the limitations of PHP as a platform and its workaround. - Creating database schemas that represent and support business processes. - Familiarity with SQL/NoSQL databases and their declarative query language. - Proficient understanding of code versioning tools, such as Gi.

Role & responsibilities JOB DESCRIPTION Strong on programming languages like Python , Java Must have one cloud hands-on experience ( GCP preferred) Must have: Experience working with Dockers Must have: Environments managing (e.g venv, pip, poetry, etc.) Must have: Experience with orchestrators like Vertex AI pipelines, Airflow, etc Must have: Data engineering, Feature Engineering techniques Proficient in either Apache Spark or Apache Beam or Apache Flink Must have: Advance SQL knowledge Must be aware of Streaming concepts like Windowing , Late arrival , Triggers etc Should have hands-on experience on Distributed computing Should have working experience on Data Architecture design Should be aware of storage and compute options and when to choose what Should have good understanding on Cluster Optimisation/ Pipeline Optimisation strategies Should have exposure on GCP tools to develop end to end data pipeline for various scenarios (including ingesting data from traditional data bases as well as integration of API based data sources). Should have a Business mindset to understand data and how it will be used for BI and Analytics purposes. Should have working experience on CI/CD pipelines, Deployment methodologies, Infrastructure as a code (eg. Terraform) Good to have, Hands-on experience on Kubernetes Good to have Vector based Database like Qdrant Experience in working with GCP tools like: Storage: CloudSQL , Cloud Storage, Cloud Bigtable, BigQuery, Cloud Spanner, Cloud DataStore, Vector database Ingest : Pub/Sub, Cloud Functions, AppEngine, Kubernetes Engine, Kafka, Micro services Schedule: Cloud Composer, Airflow Processing: Cloud Dataproc, Cloud Dataflow, Apache Spark, Apache Flink CI/CD: Bitbucket+Jenkins / Gitlab, Infrastructure as a tool: Terraform

:. Implementation, Development & customization of Oracle Banking Digital Experience (OBDX) / Oracle FLEXCUBE Direct Banking (FCDB) project.. Developing REST APIs.. Analyzing & understanding requirement.. Develop code as per the coding standards.. Code debugging and providing efficient fixes.. Fine tuning the code to improve on performance.. Qualification And Experience. Excellent design and coding skills in Digital Banking implementation & development.. Minimum 2 years of experience in Internet Banking Application implementation /customization / Development using OBDX / Flexcube Direct Banking (FCDB).. Good analysis, interpersonal & communication skills.. Ability to multi-task in a dynamic work environment.. Experience working with Web logic Application Server, Oracle Database.. Hands-on experience in working with XML, XSLT, SOAP, RESTful Web Services, JSON.. Should be proficient in Core Java and Advanced Java.. Sound experience in one of the frameworks Struts, Spring or similar.. Experience in KnockoutJS is must.. Comfortable working in a fast-moving agile environment.. Bachelor's / Master's (preferred) in Computer Science with Strong communication skills.. (ref:hirist.tech). Show more Show less

Role Expectations: As a Senior MLOps Engineer, you will be responsible for a wide range of engagements, listed below: Can guide the team to build a scalable MLOps platform and work with business architects to implement and expand the MLOps setup. Has worked on deploying ML models to production and has experience with model monitoring, inferencing, drift concepts, feature stores, etc. Has a good understanding of how ML algorithms work and how to debug issues in the code. Has deployed applications using containers and container orchestration Manages conversations with client stakeholders to understand requirements and translate them into technical outcomes. Responsible for bridging the gap between machine learning and software engineering, focusing on deployment, scaling, and management of ML models in production environments. A developer focused on streamlining the process of developing, deploying, and maintaining ML systems to ensure they are efficient, scalable, and reliable. Has a strong conceptual understanding of the ML lifecycle and various ML algorithms. Has worked on at least one cloud platform and its ML-as-a-Service offerings. Qualifications: Technical: Strong understanding of DevOps practices and skilled in developing end-to-end CI/CD pipelines • Execution knowledge of data modeling, databases (SQL and NoSQL), software development lifecycle practices, unit testing, functional programming, etc. Experience with one or more ML-as-a-Service platforms, such as Azure DevOps, Dataiku, or equivalent open-source tools Proficient in at least one programming language used in data engineering, such as Python Strong knowledge of Snowflake Experience working on at least one cloud platform Non-Technical: Good business Logical thinking and problem-solving Ability to collaborate effectively Capable of analysing problems and developing actionable, tactical plans quickly Good managerial skills and team leadership capabilities Strong verbal and written communication skills Good stakeholder management skills Exercises independent judgment within defined practices and procedures Demonstrated ability to mentor juniors

We are looking for a skilled and passionate Senior .NET Developer with strong expertise in cloud technologies, particularly Azure, and experience in building scalable microservices and APIs. The ideal candidate should have hands-on experience with Kubernetes (preferably Azure Kubernetes Services), Azure Storage, and CosmosDB, along with a good understanding of AI-driven solutions. This role requires excellent communication skills, a proactive attitude towards learning, and the ability to coordinate effectively with both onsite and offshore teams. Key Responsibilities: Design, develop, and maintain scalable and robust REST APIs and Microservices using C# and ASP.NET. Deploy and manage applications using Kubernetes or Azure Kubernetes Services (AKS). Work with Azure cloud services including Azure Storage, CosmosDB, and other Azure-native tools. Collaborate closely with cross-functional teams in an onsite/offshore model. Participate in architecture reviews and contribute to decision-making for cloud-based solutions. Explore AI integration opportunities and stay updated on modern development practices. Ensure performance, quality, and responsiveness of applications. Engage in troubleshooting, optimization, and support for existing systems. Maintain best practices in coding, testing, and deployment. Required Skills & Qualifications: Proficiency in C# and ASP.NET with experience in designing scalable enterprise-level applications. Hands-on experience with Azure Kubernetes Services (AKS) or Kubernetes. Strong understanding of Microsoft Azure and Azure Storage solutions. Experience with CosmosDB for cloud-based applications. Proficient in building and consuming REST APIs and working with Microservices architecture. Prior Microsoft ecosystem experience is a plus. Familiarity or foundational knowledge of AI technologies is desirable. Excellent verbal and written communication skills. Experience in onsite/offshore coordination. Self-driven, enthusiastic about continuous learning and growth.

Strong in Python with libraries such as polars, pandas, numpy, scikit-learn, matplotlib, tensorflow, torch, transformers • Must have: Deep understanding of modern recommendation systems including two-tower , multi-tower , and cross-encoder architectures • Must have: Hands-on experience with deep learning for recommender systems using TensorFlow , Keras , or PyTorch • Must have: Experience generating and using text and image embeddings (e.g., CLIP , ViT , BERT , Sentence Transformers ) for content-based recommendations • Must have: Experience with semantic similarity search and vector retrieval for matching user-item representations • Must have: Proficiency in building embedding-based retrieval models , ANN search , and re-ranking strategies • Must have: Strong understanding of user modeling , item representations , temporal/contextual personalization • Must have: Experience with Vertex AI for training, tuning, deployment, and pipeline orchestration • Must have: Experience designing and deploying machine learning pipelines on Kubernetes (e.g., using Kubeflow Pipelines , Kubeflow on GKE , or custom Kubernetes orchestration ) • Should have experience with Vertex AI Matching Engine or deploying Qdrant , F AISS , ScaNN , on GCP for large-scale retrieval • Should have experience working with Dataproc (Spark/PySpark) for feature extraction, large-scale data prep, and batch scoring • Should have a strong grasp of cold-start problem solving using metadata and multi-modal embeddings • Good to have: Familiarity with Multi-Modal Retrieval Models combining text, image, and tabular features • Good to have: Experience building ranking models (e.g., XGBoost , LightGBM , DLRM ) for candidate re-ranking • Must have: Knowledge of recommender metrics (Recall@K, nDCG, HitRate, MAP) and offline evaluation frameworks • Must have: Experience running A/B tests and interpreting results for model impact • Should be familiar with real-time inference using Vertex AI , Cloud Run , or TF Serving • Should understand feature store concepts , embedding versioning , and serving pipelines • Good to have: Experience with streaming ingestion (Pub/Sub, Dataflow) for updating models or embeddings in near real-time • Good to have: Exposure to LLM-powered ranking or personalization , or hybrid recommender setups • Must follow MLOps practices version control, CI/CD, monitoring, and infrastructure automation GCP Tools Experience: ML & AI : Vertex AI, Vertex Pipelines, Vertex AI Matching Engine, Kubeflow on GKE, AI Platform Embedding & Retrieval : Matching Engine, FAISS, ScaNN, Qdrant, GKE-hosted vector DBs (Milvus) Storage : BigQuery, Cloud Storage, Firestore Processing : Dataproc (PySpark), Dataflow (batch & stream) Ingestion : Pub/Sub, Cloud Functions, Cloud Run Serving : Vertex AI Online Prediction, TF Serving, Kubernetes-based custom APIs, Cloud Run CI/CD & IaC : GitHub Actions, GitLab CI