12 Aug
|
Elektrobit Automotive
|
India
12 Aug
Elektrobit Automotive
India
Overview:
We are looking for a Senior Expert – Agentic AI Development with 10+ years of software engineering experience and strong 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.
Responsibilities:
Key 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.
Qualifications:
Experience
- 8+ 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.
- Solid 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.
📌 Expert - Agentic Development & Automation (India)
🏢 Elektrobit Automotive
📍 India