Job Duties and Responsibilities:

• Collaborate with product owners, data scientists, architects, and business teams to understand AI/ML requirements.
• Translate business needs into technical specifications, acceptance criteria, performance targets, and operational requirements.
• Design scalable and secure APIs, microservices, data flows, batch pipelines, and event-driven integrations.
• Develop backend services using Python and build REST APIs that expose AI and machine- learning capabilities.
• Integrate applications with ML models, LLMs, vector databases, enterprise systems, cloud services, databases, and messaging platforms.
• Implement RAG pipelines, embeddings, semantic search, vector search, and agent-based workflows.
• Work with data scientists to package, deploy, version, and manage trained models across cloud and internal platforms.
• Develop preprocessing, post-processing, data-cleaning, transformation, and validation pipelines.
• Maintain consistency between training and production data while addressing schema changes, missing data, and data-quality issues.
• Implement validation, exception handling, logging, authentication, authorization, encryption, and audit controls.
• Write unit, integration, API, performance, regression, and user-acceptance tests.
• Validate model accuracy, confidence scores, fallback behavior, hallucinations, bias, prompt injection, and sensitive-data leakage..
• Containerize applications using Docker, deploy them to Kubernetes or cloud platforms, and support controlled releases and rollbacks.
• Monitor application and model performance, investigate production incidents, ensure regulatory compliance, conduct reviews, and maintain technical and operational documentation.
• Establish and enforce technical standards, architectural principles, and coding best practices.
• Serve as the primary technical liaison for cross-functional stakeholders across Finance, Product, and Operations.
• Perform comprehensive code reviews to ensure quality, maintainability, and security.
• Drive incident management, root cause analysis, and continuous improvement initiatives.
• Break down complex requirements into well-defined engineering tasks and delivery milestones.
• Proactively identify and address technical debt, balancing immediate delivery needs with long- term system sustainability.
• Co-ordinate with offshore and onshore teams resolved common challenges and discussed daily ticket status updates.

Technologies Involved / Skills required for the position:

• Strong programming skills, including object-oriented programming, data structures, exception handling, and performance optimization.
• Experience with machine-learning frameworks such as TensorFlow, PyTorch, Scikit-learn and Hugging Face.
• Knowledge in building RAG solutions using LangChain, LangGraph, LlamaIndex, and document-processing pipelines.
• Knowledge of vector databases such as Pinecone, Chroma, FAISS, Weaviate, OpenSearch, and pgvector.
• Experience integrating AI models through OpenAI, Anthropic, Gemini, AWS Bedrock, Azure OpenAI, or Hugging Face APIs.
• Strong backend and REST API development experience using FastAPI or similar frameworks.
• Experience with data-processing technologies, including Pandas, NumPy, PySpark, SQL, and data-validation tools.
• Knowledge of relational and NoSQL databases such as PostgreSQL, MongoDB, or DynamoDB.
• Experience with messaging and event-driven technologies such as Kafka, RabbitMQ, AWS SQS, SNS, and EventBridge.
• Experience deploying AI/ML applications using Docker, Kubernetes, serverless services, and cloud platforms.
• Understanding of MLOps practices, including model versioning, experiment tracking, CI/CD, automated testing, rollback, and monitoring.
• Experience monitoring application performance, model drift, data drift, prediction quality, latency, token usage, and cloud cost.
• Knowledge of AI security, responsible AI, privacy, model governance, explainability, and regulatory compliance.
• Excellent problem-solving, architecture, code-review, documentation, mentoring, communication, and stakeholder-management skills.