Senior AI Solutions Engineer | 3-6 Years | Bengaluru

Ovii's Interpretation of the Role

Senior AI Solutions Engineer building production‑grade LLM, RAG and Agentic AI systems for enterprise customers. Owns end‑to‑end delivery from design through deployment, collaborating with global teams and clients.

Role Snapshot

• Customer‑facing AI engineering
• Production AI system delivery
• Python & LLM expertise
• Hybrid Bengaluru location

Must-Have Requirements

• Python (4+ years hands‑on)
• LLM framework experience (LangChain, LangGraph, CrewAI, AutoGen or similar)
• RAG pipeline and prompt engineering knowledge
• API, distributed systems and cloud platform experience (AWS/Azure)
• Strong debugging and problem‑solving ability
• Python development
• LLM and RAG implementation
• Cloud API integration

Nice-to-Have Signals

• FastAPI (preferred)
• Customer‑facing implementation experience (plus)
• Familiarity with PostgreSQL, Elasticsearch, Vector DBs
• Agentic AI systems exposure
• Streaming systems (Kafka, Kinesis)
• ServiceNow or Salesforce integration experience
• Customer‑facing solutions engineering

Work Setup

• Location: Bengaluru, India
• Work mode: HYBRID
• Employment type: Full-Time

Eligibility Gates

• Visa sponsorship: unknown

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Education requirement
• Certifications
• Relocation
• Notice period
• Travel
• Security clearance
• Coding test
• Portfolio
• GitHub
• Writing sample
• Cover letter

What You'll Likely Work On

• Design, build, and deploy AI solutions using Python, LLMs and Agentic AI
• Implement and tune RAG pipelines and AI workflows
• Create integrations and custom tools for enterprise platforms
• Improve system performance, latency and scalability
• Develop streaming pipelines and scalable architectures
• Configure AI agents and troubleshoot production issues
• Collaborate directly with customers to solve operational problems
• Contribute to core platform enhancements and product roadmap

Good Fit If You Have

• Enjoys end‑to‑end ownership of AI projects
• Thrives on ambiguous, real‑world enterprise challenges
• Focuses on production impact, performance and scalability