Role: Senior Practice Manager AI/LLM & Python
Experience: 12- 15+ years
Location: Hyderabad, 5 days WFO
We are seeking a Senior Practice Manager to build, scale, and lead an AI/LLM and fullstack Python practice delivering productiongrade, enterprise AI solutions across multiple business units. This is a highimpact leadership role that blends practice building, technical solutioning, commercial ownership, and handson depth.
You will define the technical and commercial backbone of our AI offeringsestablishing reusable accelerators, reference architectures, delivery standards, and gotomarket solutionswhile mentoring highperforming, crossfunctional teams. This role demands both strategic thinking and execution rigor, with accountability for quality, scalability, security, and cost efficiency of AI solutions.
Key Responsibilities
Practice & Capability Building
- Build and scale an AI/LLM & Python practice from ground up, including talent, assets, and delivery frameworks
- Define reference architectures, accelerators, coding standards, and best practices for LLM and AI applications
- Establish MLOps and LLMOps frameworks ensuring reliability, scalability, governance, and cost optimization
- Partner with leadership to shape AI centerofexcellence (CoE) and longterm roadmaps
Technical & Solution Leadership
- Architect and oversee productiongrade AI/LLM applications using Python and modern fullstack frameworks
- Lead solutioning across:
- LLM application patterns (RAG, agents, tool use, finetuning)
- Multiagent and agentic AI systems
- Secure AI architectures and responsible AI practices
- Review and guide designs for performance, security, observability, and cost efficiency (tokens, infra, APIs)
Commercial & GTM Ownership
- Shape and own AI/LLM gotomarket offerings, pitches, and solution narratives
- Support presales, client workshops, and executive presentations
- Drive revenue growth, margin control, and delivery excellence for the practice
People & Delivery Leadership
- Mentor architects, engineers, data scientists, and MLOps teams
- Build and lead crossfunctional squads across engineering, data, and product
- Ensure ontime, highquality delivery across global engagements
Experience
- 1215+ years of overall experience with strong recent focus on AI/ML and LLMbased systems
- Proven experience in practice building, not only project delivery
- Track record of owning endtoend solutioning and enterprise delivery
Technical Expertise
- Expertlevel Python for AI and fullstack development
- Deep handson experience with:
- LLM application development (RAG, prompt engineering, agents, orchestration)
- MLOps / LLMOps, CI/CD, monitoring, model lifecycle management
- Cloudnative architectures on Azure (mandatory)
- Strong understanding of token economics, cost optimization, and scaling strategies
- Experience building secure, compliant, and resilient AI systems
Good to Have
- Exposure to AWS and/or GCP
- Experience with lowcode/nocode or automation platforms
- Multidomain and global client exposure
