AI Engineer – Agentic AI & GenAI

Experience: At least 3 years of relevant experience
Employment Type: Full-time
We are seeking an experienced Agentic AI / Generative AI Engineer with at least 3 years of relevant experience in developing AI-powered applications, LLM solutions, and intelligent automation systems.
The ideal candidate will have hands-on experience with AI agents, retrieval-augmented generation (RAG), LLM orchestration frameworks, and cloud-based AI platforms. This role will focus on building scalable, secure, and production-ready AI solutions that improve business processes and operational efficiency.
Key Responsibilities
Design, develop, and deploy AI agents and multi-agent systems for business process automation.
Build LLM-powered applications using frameworks such as LangChain, LangGraph, and LlamaIndex.
Develop and optimize RAG pipelines using embeddings, vector databases, and semantic search.
Integrate LLMs from OpenAI, Anthropic Claude, and AWS Bedrock into enterprise applications.
Develop agentic workflows involving tool calling, API integrations, and autonomous task execution.
Build and maintain backend services and APIs supporting AI applications.
Evaluate and improve AI model accuracy, response quality, latency, and cost efficiency.
Implement AI guardrails, data privacy controls, and output validation mechanisms.
Collaborate with engineering, product, and business teams to deliver practical AI solutions.
Monitor, troubleshoot, and continuously optimize deployed AI systems.
Required Qualifications
At least 3 years of relevant professional experience in AI/ML engineering, Generative AI, software engineering with AI application development, or a related field.
Strong programming skills in Python and experience developing backend applications or APIs.
Hands-on experience building and deploying LLM-powered applications.
Practical experience with AI frameworks such as LangChain, LangGraph, or LlamaIndex.
Experience working with LLM platforms such as OpenAI, Anthropic Claude, or AWS Bedrock.
Understanding of RAG architectures, vector databases, embeddings, and semantic search.
Experience integrating APIs, databases, and external systems into AI applications.
Knowledge of prompt engineering, function calling, structured outputs, and agent orchestration.
Familiarity with cloud platforms and deploying applications in production environments.
Strong analytical, troubleshooting, and problem-solving skills.
Preferred Qualifications
Experience developing multi-agent AI systems and advanced agentic workflows.
Familiarity with vector databases such as Pinecone, Weaviate, Milvus, or Chroma.
Experience with AWS services, particularly Amazon Bedrock.
Knowledge of AI evaluation, observability, monitoring, and safety guardrails.
Familiarity with Docker, CI/CD pipelines, and cloud-native deployment.
Experience delivering AI solutions in BFSI, healthcare, retail, insurance, manufacturing, or Global Capability Centers (GCCs).
Technical Skills
AI Technologies: Agentic AI, Generative AI, LLMs, RAG
Frameworks: LangChain, LangGraph, LlamaIndex
LLM Platforms: OpenAI, Anthropic Claude, AWS Bedrock
Data Technologies: Vector databases, embeddings, semantic search
Programming: Python, REST APIs, backend development
Deployment: AWS, Docker, CI/CD, monitoring and observability
Ideal Candidate Profile
The ideal candidate has at least 3 years of relevant experience and can translate AI concepts into reliable, production-ready applications. They should be comfortable developing AI agents, integrating enterprise data sources, optimizing LLM workflows, and collaborating with cross-functional teams to solve business challenges.
Industry Experience
Experience in one or more of the following sectors is advantageous:
Banking, Financial Services, and Insurance (BFSI)
Healthcare
Retail and e-commerce
Manufacturing
Global Capability Centers (GCCs)

Work arrangement
Yes