AI & Data Science Engineer

Role: AI & Data Science Engineer

Employment Type: Full Time Permanent

Location: Pune - Kharadi (Onsite)

Notice: Immediate to 15 days

About the Role:

We are hiring an experienced AI & Data Science Backend Engineer to lead a team of developers and take ownership of complex agentic AI projects with 3+ years experience. This role involves architecting intelligent systems, managing deployments, and ensuring successful delivery of enterprise-grade AI solutions. If interested please share your resume to keerthika@glimmora.ai

Key Responsibilities

Lead and mentor a team of backend developers, including task allocation and code reviews

Architect and develop complex multi-agent orchestration systems

Design and implement autonomous AI workflows with reasoning, planning, and execution capabilities

Build advanced tool-use patterns, function calling, and persistent agent memory

Design and optimize RAG architectures using vector databases for enterprise-scale retrieval

Design, manage, and optimize databases including schemas, queries, and data pipelines

Deploy and manage LLMs in cloud, on-premise, and air-gapped environments

Own end-to-end deployment pipelines including CI/CD, containerization, and server management

Manage GPU infrastructure, CUDA environments, and model inference optimization

Design scalable APIs and microservices for high-concurrency AI systems

Plan project scope, define milestones, and manage technical delivery timelines

Troubleshoot complex production issues across AI models, databases, and infrastructure

Communicate technical progress, risks, and blockers to stakeholders and clients

Required Skills

Python (3+ years) with strong backend and system design experience

Deep expertise in agentic AI (React, planning loops, reflection, tool use)

Experience with LangChain, Semantic Kernel, AutoGen, CrewAI, LangGraph

LLM integrations: OpenAI, Azure OpenAI, Claude, Llama, Mistral

Strong SQL skills with performance tuning

Database management: PostgreSQL, MySQL, SQL Server

Vector databases: Pinecone, Weaviate, ChromaDB, Qdrant, FAISS

FastAPI or Flask

Docker, CI/CD, Linux

Team leadership and mentoring experience

Good to Have

Kubernetes

Air-gapped deployment experience

GPU/CUDA optimization

AWS, Azure, or GCP

MongoDB, Redis

High-concurrency system experience

Agile project management

What Were Looking For

A technically strong engineer who can own complex AI projects end-to-endfrom architecture and database design to deployment and scalingwhile making sound technical decisions and elevating the teams overall capabilities.