KASHII UPDATEZ Everyday Student Requirements & Python Coding Tutorials by Python Kashi
N #3153
Applications open Full-Time Job

AI/Python Engineer - Immediate Hiring - Innominds Software -Bangalore

Innominds Software

  • Bengaluru, India
  • Competitive Package (Best in Industry)
  • 5-10 Yrs
  • Posted Today
HR
Recruiter contact
Recruiter / hiring contact
No public email in this post. Use a source-linked contact instead.

About the role

Job Title: Senior AI / Python Engineer @

Innominds Experience

5-12

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 β€”Delivery Director, AVP, or beyond. You own your arc. Customer Intimacy at Scale You will have direct access to senior customer leadership β€” 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.

Eligibility & process

Who can apply

Experience: 5-10 Yrs. Open to matching qualifications.

Skills & stack

Machine Learning SQL Science Languages Machine Hiring Python Next.js

Selection process

  1. Online Assessment / Technical Interview Rounds / HR Review

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Machine Learning, SQL, Science, Languages, Machine, Hiring, Python, Next.js) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Innominds Software Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join Innominds Software as a AI/Python Engineer - Immediate Hiring - Innominds Software -Bangalore?
Highlight Innominds Software's market reputation, recent tech innovations, and how your skills in Machine Learning directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Innominds Software Competitive Package (Best in Industry)
Recruiter Resume Apply
Chat Chat with Kashii