Generative AI Engineer

About Client :-

Our client is a French multinational information technology (IT) services and consulting company, headquartered in Paris, France. Founded in 1967, It has been a leader in business transformation for over 50 years, leveraging technology to address a wide range of business needs, from strategy and design to managing operations.

The company is committed to unleashing human energy through technology for an inclusive and sustainable future, helping organizations accelerate their transition to a digital and sustainable world.

They provide a variety of services, including consulting, technology, professional, and outsourcing services.

Job Details:-

location : Pan India

Mode Of Work : Hybrid

Notice Period : Immediate Joiners

Experience : 6-10yrs

Type Of Hire : Contract to Hire

Must Have Skills-

We are looking for Developers with strong hands-on experience in Generative AI and cloud-native application development. The ideal candidate will have a proven track record of building real-world applications using LangChain, LLMs, AWS Bedrock, and vector databases like pgvector. This is a hands-on development role focused on building production-grade AI-powered applications.

Key Responsibilities:

Build and deploy Generative AI applications using LangChain, LLMs, and AWS Bedrock.

Integrate Titan embeddings, vector database, knowledge graphs and Query Retrievals into scalable backend services.

Develop and maintain Python-based APIs and microservices.

Use AWS Lambda, S3, ECS, SQS, and STS to build serverless, cloud-native applications.

Collaborate with AI/ML engineers, product managers, and DevOps teams to deliver end-to-end features.

Write clean, testable, and maintainable code following best practices.

Participate in code reviews, agile ceremonies, and continuous improvement initiatives.

Required Skills & Qualifications:

1 year of hands-on software development experience.

Expertise in Python and backend development.

Strong experience with LangChain, LLMs (e.g., Claude, GPT), and RAG (Retrieval-Augmented Generation).

Strong experience with AWS Bedrock and Titan embeddings.

Experience with vector databases such as pgvector, Atlas, FAISS, or Pinecone.

Solid understanding of RESTful APIs, microservices, and cloud-native design.

Experience with code assistant tools such as GitHub Copilot, Windsurf, or similar.

Experience working in Agile/Scrum teams.

Nice to Have:

Frontend development experience with Angular or ReactJS.

Experience with CI/CD, Docker, and infrastructure as code (e.g., Terraform).

Exposure to embedding pipelines, and data privacy/security in AI applications.

Develop Agentic AI workflows using LangGraph to orchestrate multi-step reasoning and decision-making.