Senior AI Engineer – Generative AI and AWS
LetzBizz
Date: 2 hours ago
City: Chennai, Tamil Nadu
Contract type: Full time
6–8 Years
Hybrid / Remote
Chennai / Kerala / Tamil Nadu
Hiring Partner: LetzBizz
Client Location: Poland
Location: Chennai / Kerala / Tamil Nadu
Work Mode: Hybrid or Remote
Apply: [email protected]
About The Role
We are looking for an experienced engineer to develop and deploy AI applications on AWS, combining generative AI, autonomous agents and machine learning. You will take solutions from experimentation through production, with responsibility for reliability, evaluation, security and ongoing operation.
Role: Hands-on engineering with client interaction
Preferred domain: Life Sciences or Healthcare
Key Responsibilities
Delivering secure, reliable AI applications with measurable quality, effective agent execution, monitored performance and cost, reusable components, and a successful transition from proof of concept to production.
How to Apply
Interested Candidates Can Share Their Updated Resumes At
[email protected]
Please mention Senior AI Engineer – Generative AI and AWS in the email subject.
Share the job
Hybrid / Remote
Chennai / Kerala / Tamil Nadu
Hiring Partner: LetzBizz
Client Location: Poland
Location: Chennai / Kerala / Tamil Nadu
Work Mode: Hybrid or Remote
Apply: [email protected]
About The Role
We are looking for an experienced engineer to develop and deploy AI applications on AWS, combining generative AI, autonomous agents and machine learning. You will take solutions from experimentation through production, with responsibility for reliability, evaluation, security and ongoing operation.
Role: Hands-on engineering with client interaction
Preferred domain: Life Sciences or Healthcare
Key Responsibilities
- Develop AI agents capable of planning tasks, using tools, maintaining context and coordinating workflows, including human approvals where required.
- Build retrieval-augmented generation (RAG) solutions covering document ingestion, chunking, embeddings, metadata, vector and hybrid search, reranking and grounded responses.
- Connect AI applications to enterprise APIs, data platforms and AWS services through secure, permission-controlled integrations.
- Implement prompts, structured responses, conversation state, routing, fallbacks and error recovery.
- Establish automated evaluations for response accuracy, groundedness, retrieval relevance, safety, task completion, latency and cost.
- Apply guardrails, personal-data protection, audit logging and human review controls.
- Develop conventional ML workflows where needed, including feature engineering, training, tuning, deployment, monitoring and retraining.
- Implement testing, CI/CD, infrastructure automation, model and prompt versioning, observability, alerting and operational documentation.
- Work with architects, data engineers, application teams, domain specialists and client stakeholders to define and deliver testable capabilities.
- Support demonstrations, user acceptance testing, production releases, troubleshooting, performance improvements and knowledge transfer.
- 6–8 years of experience in AI/ML, data science or software engineering, with strong Python programming and production engineering skills.
- Hands-on experience with Amazon Bedrock, including foundation models, Knowledge Bases, Guardrails, model evaluation and agent or tool-calling implementations.
- Strong practical understanding of GenAI and RAG, including embeddings, vector databases, retrieval strategies, reranking and prompt engineering.
- Experience with agent orchestration, planning, memory, tool invocation, human approval workflows and multi-agent coordination.
- Working knowledge of supervised learning, feature engineering, model evaluation, deployment, drift detection and monitoring.
- Experience integrating solutions using AWS Lambda, Step Functions, OpenSearch, S3 and APIs, with secure access to enterprise data.
- Hands-on experience with Git, automated testing, CI/CD, containers and infrastructure or configuration automation.
- Ability to work directly with US-based business and technical stakeholders, explaining solution behaviour, evaluation results, limitations and engineering trade-offs.
- Amazon SageMaker for developing and operating ML pipelines.
- Amazon Bedrock AgentCore, Strands Agents, LangGraph, LangChain or comparable agent frameworks.
- OpenSearch vector search or knowledge graphs.
- AI delivery in Life Sciences or Healthcare, particularly research, clinical operations, medical affairs, commercial operations, manufacturing or pharmacovigilance.
- Familiarity with regulated environments and GxP requirements.
- Responsible AI, red teaming, synthetic evaluation data, LLM observability, fine tuning or multimodal applications.
- Terraform or AWS CDK.
- Relevant AWS certifications in AI or machine learning.
Delivering secure, reliable AI applications with measurable quality, effective agent execution, monitored performance and cost, reusable components, and a successful transition from proof of concept to production.
How to Apply
Interested Candidates Can Share Their Updated Resumes At
[email protected]
Please mention Senior AI Engineer – Generative AI and AWS in the email subject.
Share the job
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