Antier
From Antier's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
About the Role The Technical Program Manager owns delivery of Antier's AI engagements end to end, technically and functionally.
The Technical Program Manager owns delivery of Antier's AI engagements end to end, technically and functionally. This is a hands-on engineering leadership role, not a project coordination role: the person owns the technical design, approves architecture before build, works on the hardest problems, and runs delivery across multiple concurrent engagements through to handover.
Own the technical design across engagements – architecture, model approach, data, integration and deployment.
Review and approve every solution design before build starts and reject approaches that will not scale or hold up in production.
Work hands-on on the hardest problems and unblock teams technically.
Set and enforce engineering standards: code quality, testing, documentation, release and deployment.
Evaluate models, frameworks and tools, and decide what the division adopts.
Own end-to-end delivery of concurrent engagements: plan, milestones, dependencies, resourcing and schedule.
Identify technical and delivery risks early and drive them to resolution.
Allocate engineering capacity across engagements, and lead and mentor the teams.
Own requirement and acceptance quality, working with the BA team, so that what is built solves the client's actual problem.
Manage scope changes through change control, with revised effort and timeline.
Act as the technical and delivery counterpart to the client, and report project health to division leadership.
Engineering or technical academic background – B.Tech, BE, MCA, MSc or equivalent. Business, management or sales profiles are not suitable.
Minimum 8 years overall, with at least 4 years building and shipping AI or ML systems.
Currently hands-on: writes and reviews code, owns architecture, and can take the hardest problem on a project themselves.
Deep practical knowledge of AI and ML: model development and evaluation, generative AI and LLM-based systems, RAG, computer vision, and the data engineering behind them.
Strong software engineering fundamentals and production deployment experience across cloud and on-premise, including MLOps and release management.
At least 3 years running delivery across multiple teams or concurrent projects, including estimation, resourcing and schedule ownership.
Experience leading engineering teams and working directly with clients through delivery.
Excellent communication, spoken and written, across technical and business audiences.
Delivery experience with enterprise clients in India, GCC, UK or Europe.
Experience with on-premise or regulated-environment AI systems, IoT or industrial data platforms.
Scores your resume against this job the way resume scanners do: the job's hard and soft skills, searchability, recruiter tips and formatting.
Create a free account to see your score. Your resume stays in this browser until then, and we never store it.
Already a member? Sign in