Overview:

We are looking for a Senior Expert – Agentic AI Development with 10+ years of software engineering experience and robust expertise in Generative AI and Agentic AI solutions. The role focuses on designing, developing, and deploying enterprise-grade AI agents, multi-agent systems, and AI-powered workflow automation solutions that deliver measurable business value.

Experience - 10years

Openings - 1

Responsibilities:

Agentic AI Development

- Design and develop AI agents and multi-agent systems for enterprise use cases.
- Build AI assistants, copilots, and workflow automation solutions.
- Implement agent orchestration, planning, memory, reasoning, and tool integration capabilities.
- Develop reusable agent frameworks, skills, and components.

GenAI & LLM Engineering

- Design and implement RAG-based solutions using enterprise knowledge sources.
- Integrate and optimize LLMs for business applications.
- Perform prompt engineering, evaluation, and performance optimization.

Enterprise Integration & Deployment

- Integrate AI agents with enterprise applications, APIs, databases, and cloud platforms.
- Collaborate with MLOps teams for deployment, monitoring, and scaling of AI solutions.
- Ensure security, governance, and responsible AI practices.





Technical Leadership

- Mentor engineers and share best practices in Agentic AI development.
- Support architecture reviews, technology evaluations, and innovation initiatives.
- Contribute to AI standards, frameworks, and reusable assets.

Candidate Profile

Experience

- 10+ years of software engineering experience.
- 3+ years of hands-on experience in Generative AI/LLM-based applications.
- Proven experience delivering AI solutions in production environments.

Technical Skills

- Agentic AI frameworks: LangGraph, LangChain, CrewAI, AutoGen, OpenAI Agents SDK.
- LLMs, Prompt Engineering, RAG architectures, and Vector Databases.
- Strong Python programming and API development skills.
- Cloud platforms (Azure, AWS, or GCP).
- Docker, Kubernetes, CI/CD, and AI deployment practices.
- Understanding of AI governance, security, and observability.

Success Measures

- Successful deployment of AI agents into production.
- Improved automation and productivity through AI solutions.
- High-quality, scalable, and secure AI implementations.

Adoption and business impact of delivered Agentic AI solutions

📌 Agentic AI Engineer (Bengaluru)
🏢 Elektrobit Automotive
📍 Bengaluru