Python Lead (AI/ML)
Posted Updated
Description
Python Lead (AI/ML)
Delivery Team | 7+ Years Experience
Location: [Hyderabad/ Remote / Hybrid]
Job Summary
We are looking for an experienced Python Lead to own the end-to-end delivery of client-facing ML and Python-based solutions — from initial demo and proof-of-concept through deployment and post-launch support. This role combines hands-on technical ownership with client delivery accountability, ensuring solutions are built to scope, tested to standard, and delivered on time. The lead will work closely with clients and partners, owning each engagement from project kick-off, planning and execution through to closure, including all client communications.
Key Responsibilities
Python Engineering & Technical Leadership
- Lead the design and development of Python-based applications and ML pipelines using frameworks like Django, Flask, or FastAPI, ensuring efficient, production-grade code.
- Own database design and integration (SQL, PostgreSQL, or MongoDB) as part of the overall solution architecture.
- Mentor and guide junior Python developers through code reviews, technical guidance, and knowledge-sharing.
- Ensure adherence to coding standards, security protocols, and CI/CD best practices (Git, automated pipelines).
- Guide the ML lifecycle — data preparation, model training, evaluation, deployment, and monitoring — applying GenAI/LLM capabilities where relevant.
Solution Delivery & Client Ownership
- Own end-to-end delivery of client solutions — from demo and POC through implementation and deployment, following a phased approach — while defining in-scope/out-of-scope parameters and managing delivery against agreed project timelines.
- Act as the primary technical point of contact for client-facing engagements, managing expectations and ensuring deliverables meet the agreed scope.
Project Kick-off, Planning & Execution
- Kick-off: Plan and lead project kick-off with client and partner stakeholders, aligning on objectives, success metrics, roles, governance, and communication cadence.
- Planning: Build the project plan covering milestones, release schedule, resourcing, and sprints; contribute to estimates and SOWs; maintain a risk, assumptions, issues, and dependencies (RAID) log.
- Execution: Run Agile delivery against timeline, scope, and budget; manage change requests formally; coordinate QA, UAT, performance testing, RFC approvals, and production go-live.
- Closure: Deliver handover documentation and knowledge transfer, obtain client sign-off, and lead retrospectives.
Client Communication & Partner Management
- Build trusted relationships with client stakeholders, from technical teams to executive sponsors, and explain AI/ML solutions in business terms.
- Run client governance through weekly status calls, steering committee updates, and executive summaries covering progress, risks, decisions needed, and next steps.
- Handle client escalations professionally and identify opportunities to extend or expand the engagement.
- Work closely with channel partners, implementation partners, and vendors, aligning on roles, handoffs, and shared timelines, and coordinating dependencies across client, partner, and internal teams.
Quality, Deployment & Support
- Own the testing process (unit, integration, and model validation) to ensure solutions meet defined accuracy and performance benchmarks.
- Support containerization and deployment (Docker, Kubernetes) across cloud platforms such as AWS, GCP, or Azure.
- Provide post-deployment support and drive continuous optimization of deployed solutions.
- Communicate progress, risks, and roadblocks proactively to stakeholders, and maintain delivery documentation (solution design, testing metrics).
Required Skills
- 7+ years of hands-on Python development experience, with strong command over the language and its ecosystem.
- Proficiency in Django, Flask, or FastAPI, and databases such as SQL, PostgreSQL, or MongoDB.
- Experience with Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure), along with CI/CD pipelines and Git.
- Hands-on exposure to Machine Learning model development and deployment.
- Must have prior experience in a client delivery, consulting, or implementation environment — this is a mandatory requirement, not just a technical build role.
- Proven experience owning client-facing technical delivery from kick-off through planning, execution, and go-live, including scoping, SOWs, change requests, release management, and stakeholder communication.
- Experience with Agile delivery methodologies and phased/iterative implementation models.
- Strong problem-solving skills, with the ability to lead a team and mitigate delivery risks proactively.
- Experience working with channel or implementation partners, and excellent written and verbal communication for senior and executive audiences.
Educational Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field.
- Master's degree in a relevant technical discipline is a plus, though not mandatory given the experience requirement.
Preferred Qualifications
- Experience with GenAI/LLM solutions such as RAG pipelines, vector databases, or LLM APIs.
- Exposure to regulated industries such as healthcare or insurance, including data privacy and compliance (e.g., HIPAA), and security standards such as OAuth and SSO.