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Job description
Location: Noida, India
Experience: 6+ years · Positions: 1 · Reports to: Delivery / Engagement Head Role summary The POD Lead owns end-to-end delivery of AI solutions on GCP for the client. They design the solution, lead a pod of three FDEs, and are the main technical face to the client's business and IT stakeholders. Key responsibilities
Lead the pod (1 Senior FDE, 2 Junior FDEs): plan sprints, assign work, review code and unblock the team
Translate client business problems into technical solution designs and delivery plans
Architect AI solutions on GCP, including GenAI, LLM and agent-based workflows
Design voice and document management solutions: speech-to-text, text-to-speech, conversational voice agents, document extraction and classification
Own production quality: debugging of complex issues, root-cause analysis, monitoring and performance tuning
Run client workshops, demos, status reviews and steering updates
Manage scope, timelines, risks and escalations with the client and internal leadership
Set coding, security and documentation standards for the pod
Mentor and grow the Senior and Junior FDEs Required skills
GCP stack: deep hands-on experience with Vertex AI, Cloud Run, Cloud Functions, BigQuery, Cloud Storage, Pub/Sub, IAM and networking basics
Python: expert level; production APIs (FastAPI or Flask), async processing, testing and packaging
AI: GenAI and LLMs (Gemini or similar), prompt design, retrieval-augmented generation (RAG), agent frameworks, model evaluation
Voice and document management: Speech-to-Text, Text-to-Speech, Dialogflow CX or similar; Document AI, OCR and document workflows
Debugging: proven track record resolving production incidents across cloud services, logs (Cloud Logging) and traces
Communication and presentability: confident with senior client stakeholders; clear written updates; strong whiteboarding and demo skills Python & Data Structures / Algorithms (DSA) Required Skills
6+ Years in Expert-level Python programming with extensive experience in designing and building scalable enterprise applications.
Strong expertise in Object-Oriented Design, Design Patterns, Concurrency, Multi-threading, Async Programming, and Microservices Architecture.
In-depth knowledge of advanced Data Structures including Trees, Graphs, Heaps, Tries, Hash Maps, Distributed Data Structures, and Large-Scale Data Processing techniques.
Proven experience in designing efficient algorithms and optimizing systems for performance, scalability, and reliability.
Strong ability to review code, establish engineering best practices, and mentor engineering teams.
Deep understanding of computational complexity, architecture trade-offs, and software design principles.
Experience leading technical design discussions and driving engineering excellence across AI/ML and software development teams. Good to have
Google Cloud Professional certification (Cloud Architect or Machine Learning Engineer)
CI/CD and infrastructure as code (Cloud Build, Terraform)
Prior experience in a client-facing or consulting delivery role
This page helps Indian job seekers prepare for Python interviews for backend, data engineering and data analyst roles, whether you are a fresher facing your first technical round or an experienced developer aiming for a senior position. It has 60 questions in three levels, easy, medium and hard, each with a concise sample answer and, where it helps, runnable Python 3.12 code. Topics include data structures, OOP, generators, decorators, the GIL and concurrency, type hints, testing and performance. Answer each question aloud in your own words first, then compare with the sample answer and run the code to check your understanding.
Questions you may be asked
What is the difference between mutable and immutable types in Python?
What is the difference between a list and a tuple?
