Technical Lead, AI Initiatives - India

Ovii's Interpretation of the Role

Technical Lead for AI initiatives at Juniper Square, driving architecture, design, and production delivery of large‑language‑model based systems. Lead a team of engineers, partner with product and research, and shape the AI platform strategy for a fast‑growing fintech company.

Role Snapshot

• Lead AI engineering team
• Design multi‑agent and RAG architectures
• Integrate LLMs via Model Context Protocol
• Mentor engineers and enforce best practices
• Own technical road‑maps and sprint planning
• Deploy AI services on cloud platforms

Must-Have Requirements

• Python
• TypeScript/Node.js
• LLM tool integration (MCP)
• Agent frameworks (LangChain, LlamaIndex, etc.)
• RAG pipelines & vector stores
• Cloud platforms (AWS, GCP, Azure)
• API & microservice development
• Backend architecture for scalable AI services
• software engineering
• backend architecture
• LLM development
• Bachelor’s or Master’s degree in Computer Science, Engineering, AI, or related field
• Must be based in India for remote work

Nice-to-Have Signals

• Fine‑tuning LLMs
• OpenAI, Claude, or Azure OpenAI APIs
• Distributed embeddings & high‑throughput retrieval
• MLOps frameworks
• DevOps, CI/CD, Docker/Kubernetes
• fine‑tuning
• MLOps

Work Setup

• Location: India
• Work mode: REMOTE
• Remote scope: UNSPECIFIED
• Remote countries: India
• Employment type: Full-Time

Eligibility Gates

• Visa sponsorship: no

Not Specified in JD

• Salary range
• Visa sponsorship
• Relocation assistance
• Travel requirements
• Security clearance
• Coding test

What You'll Likely Work On

• Design and implement multi‑agent systems with orchestration, delegation, and tool interaction patterns
• Build scalable Retrieval‑Augmented Generation pipelines using vector databases and embedding models
• Integrate and extend Model Context Protocol tools for robust model‑tool communication
• Lead development of AI‑driven features and production‑grade LLM applications
• Create and maintain evaluation frameworks, automated testing harnesses, and continuous improvement loops
• Monitor performance, latency, cost, and reliability; drive optimization strategies
• Mentor engineers, conduct code reviews, and uphold architectural standards
• Own technical road‑maps, sprint planning, and cross‑functional delivery

Good Fit If You Have

• Proven ability to lead small‑to‑mid‑size engineering teams
• Strong communication and collaboration with product and research stakeholders
• Passion for building production‑grade AI systems that solve real‑world problems