Senior AI / Python Engineer - Innominds Software Pvt Ltd - Bangalore

Innominds Software; Chennai District, Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

Competitive compensation

Performance bonuses

ISV-First DNA

Job summary

Innominds is seeking a Senior AI / Python Engineer to design and build core platform components for an enterprise MCP platform connecting ChatGPT Enterprise to governed data in Databricks Unity Catalog. You will lead the orchestration layer, prompts, and agent configurations, ensuring production-grade quality, observability, and cost efficiency.

You will collaborate with OpenAI teams and AWS/EKS infra, own upgrades, CI/CD pipelines, and security controls while delivering scalable, low-latency

Qualifications

• 6+ years of professional software engineering experience with strong Python (3.10+) including async programming, typing, packaging, and testing (pytest).
• Hands-on experience building LLM applications: prompt engineering, tool/function calling, multi-agent/orchestration design.
• Proven ownership of a production system component (e.g., orchestration, routing, matching, or search) from design through operations.
• Experience with entity matching, NLP, or retrieval (fuzzy matching, embeddings, RAG).
• API and security fundamentals: REST, OAuth 2.0 / OIDC.
• Working knowledge of AWS (EKS, S3, CloudWatch, DynamoDB, Redis/ElastiCache), Docker, and Kubernetes.
• Strong SQL and a cloud data platform (Databricks or similar), including notebooks/PySpark.
• Git and CI/CD (GitHub Actions); track record of managing breaking dependency upgrades safely.
• Clear written and verbal communication; able to work independently in an ambiguous, fast-moving environment.

Responsibilities

• Design and build the multi-agent orchestration layer: intent classification, semantic routing, agent handoffs, and clarification flows.
• Build and evolve account and entity resolution: alias indexes, fuzzy and semantic matching, versioned swaps, and shadow-to-enforce rollouts.
• Enhance the MCP server (FastMCP): tools, agents, and new features from requirements through release.
• Write design documents before coding and document trade-offs across accuracy, latency, and cost.
• Develop and refine prompts, agent instructions, tool descriptions, and semantic examples; reduce hallucination.
• Onboard and maintain agents: vector stores, recipe files, retrieval tuning, and SQL logic against Databricks Unity Catalog.
• Instrument agents and tools with tracing; track prompt versions, token cost, latency, and quality.

Skills

Python

Async programming

Typing

Packaging

Testing

LLM apps

Production ownership

Entity matching

API security

AWS

EKS

S3

Databricks

GitHub Actions

CI/CD

Kubernetes

SQL

Tools

AWS

EKS

S3

CloudWatch

DynamoDB

Redis/ElastiCache

Docker

Kubernetes

Databricks Unity Catalog

Langfuse

OpenTelemetry

Promptfoo

GitHub Actions

OpenAI Agents SDK

LangGraph

Job description

Job Title: Senior AI / Python Engineer @ Innominds

Experience: 6-12 Years

Location: Bangalore

Work Mode - Hybrid

Senior AI / Python Engineer

Enterprise Data Platform (EDP)

Role Summary

We are hiring a Senior AI / Python Engineer for one of the AI Initiative, which delivers an enterprise MCP (Model Context Protocol) platform connecting ChatGPT Enterprise to governed data in Databricks Unity Catalog. You will design and build core platform components, including the orchestration layer, account and entity resolution, and observability. You will also enhance the MCP server, engineer and evaluate prompts and agent instructions, enable new features, and own upgrades, releases, and production quality.

Key Responsibilities

Platform development

• Design and build the multi-agent orchestration layer: intent classification, semantic routing (embedding similarity with LLM fallback), agent handoffs, and clarification flows.
• Build and evolve account and entity resolution: alias indexes, fuzzy and semantic matching, batch index publishing with versioned swaps, and shadow-to-enforce rollouts, delivered as versioned, tested Python packages.
• Enhance the MCP server (FastMCP): tools, agents, and new features from requirements through release.
• Write design documents before coding and document trade-offs across accuracy, latency, and cost.

Prompt engineering and agent configuration

• Develop and refine prompts, agent instructions, tool descriptions, and semantic examples; reduce hallucination and tool-selection errors.
• Onboard and maintain agents: configuration, vector stores and recipe files, retrieval tuning, and SQL logic against Databricks Unity Catalog.

Observability, evaluation, and quality

• Instrument agents and tools with Langfuse (or equivalent) tracing; track prompt versions, token cost, latency, and quality per agent.
• Maintain evaluation suites (e.g., Promptfoo) with LLM-as-judge grading; add regression tests for every prompt or agent change and gate releases on the results.
• Own the audit and activity pipeline (CloudWatch, S3, Databricks); use logs, traces, and user feedback to improve routing, prompts, and retrieval.

Platform lifecycle and operations

• Plan and run dependency upgrades (OpenAI Agents SDK, openai, pydantic, FastMCP): breaking-change analysis, compatibility testing, phased rollout, and rollback.
• Manage CI/CD (GitHub Actions), nonprod-to-prod promotion, configuration and secrets, and Kubernetes (EKS) rollouts.
• Integrate external services and MCPs (e.g., Salesforce/MuleSoft, APISIX-based MCPs).
• Triage and resolve production issues; write and maintain runbooks.

Scale, security, and governance

• Optimize performance and cost: concurrency, rate limiting, connection pooling, Redis caching, retries and timeouts, model selection, token usage, and multi-pod consistency.
• Implement enterprise controls: OAuth (Azure AD) with user impersonation (OBO), row-level security compatibility, input validation, prompt-injection defenses, PII handling, and audit logging.

Collaboration

• Work with the OpenAI team, AWS/EKS infrastructure, security owners, and business users.
• Use AI-assisted development and review tools while owning design decisions and verifying every change with tests.

Required Qualifications

• 6+ years of professional software engineering experience, with strong Python (3.10+): async programming, typing, packaging, and testing (pytest).
• Hands-on experience building LLM applications: prompt engineering, tool/function calling, and multi-agent or orchestration design.
• Proven ownership of a production system component (e.g., orchestration, routing, matching, or search) from design through operations.
• Experience with entity matching, NLP, or retrieval (fuzzy matching, embeddings, RAG).
• API and security fundamentals: REST, OAuth 2.0 / OIDC.
• Working knowledge of AWS (EKS, S3, CloudWatch, DynamoDB, Redis/ElastiCache), Docker, and Kubernetes.
• Strong SQL and a cloud data platform (Databricks or similar), including notebooks/PySpark.
• Git and CI/CD (GitHub Actions); track record of managing breaking dependency upgrades safely.
• Clear written and verbal communication; able to work independently in an ambiguous, fast-moving environment.

Preferred Qualifications

• Experience with Model Context Protocol (MCP), FastMCP, OpenAI Agents SDK, or comparable agent frameworks (LangChain / LangGraph).
• Experience with LLM observability and evaluation tools (Langfuse, OpenTelemetry, Promptfoo).
• Familiarity with Databricks Unity Catalog governance, row/column-level security, and metric views or semantic layers.
• Background in enterprise security: Azure AD / Entra ID, identity propagation, secrets management.
• Experience optimizing cost and latency of LLM workloads.
• Life sciences, commercial, or enterprise data domain experience.

Technology Stack

Python 3.11 FastMCP OpenAI Agents SDK / ChatGPT Enterprise Databricks Unity Catalog AWS (EKS, CloudWatch, S3, DynamoDB, Redis, ALB, WAF) Azure AD OAuth Langfuse Promptfoo GitHub Actions Docker / Kubernetes

Why Innominds?

A note for those who want more than just a job

ISV-First DNA

Innominds was purpose-built for the ISV ecosystem. We speak the language of product engineering, SaaS velocity, and platform scale not generic IT services.

Global Reach, Startup Soul

With 2,500+ engineers across the US, India, and EMEA, we combine enterprise delivery muscle with the agility and ownership culture of a growth-stage company.

Cutting-Edge Work

From AI/ML and cloud-native platforms to embedded security and digital transformation ,you will work on whats next, not what's left.

Real Career Ownership

We believe in promoting from within. Your KPIs here translate into a growth trajectory -Delivery Director, AVP, or beyond. You own your arc.

Customer Intimacy at Scale

You will have direct access to senior customer leadership - not filtered through layers. Real relationships, real impact, real accountability.

Competitive Rewards

Market-leading compensation, performance bonuses.

If you believe delivery is an art and customer trust is currency, Innominds is your stage.