Note: The job is a remote job and is open to candidates in USA. qode.world is seeking a Sr. Technical Project Manager (TPM) to drive delivery for complex, cross-functional initiatives involving AI/ML and intelligent automation. The role involves managing project execution, collaborating with various teams, and ensuring high-quality outcomes in the rollout of AI-driven solutions.
Responsibilities
- Own end-to-end project execution: plan, schedule, and drive delivery across the full project lifecycle, balancing constraints and keeping work moving forward in partnership with product and engineering counterparts
- Build and maintain project plans, track milestones, and proactively manage risks, issues, and tradeoffs—providing clear stakeholder updates with recommended solutions
- Serve as the PMO lead for the ML's agentic platform and customer facing products — the structured methodology for developing, testing, deploying, and operating AI agents within MeridianLink’s agentic architecture
- Partner with engineering leads to embed AI into each SDLC phase: requirements (AI-assisted grooming agents), development (co-pilot and Claude Code standards), testing (test-driven development metrics), and release (zero-downtime deployment, feature flag governance)
- Establish and continuously improve team processes that increase quality and productivity through process definition, education, and refinement
- Facilitate light weight agile ceremonies (planning, standups, retrospectives) and drive continuous improvement through retrospective assessments
- Use tools such as Jira (and related reporting) to support teams and enable visibility into progress, capacity, and delivery health. Bridge product and engineering AI alignment
Skills
- 7+ years of technical program management in a software engineering organization, with at least 2 years in an AI, ML, or platform transformation context
- Demonstrated experience managing AI/ML initiatives or SDLC modernization programs — not just awareness, but delivery ownership
- Fluency with AI-driven SDLC concepts: AI-assisted requirements, co-pilot/code generation tooling, test automation, agentic deployment, and observability
- Ability to translate engineering complexity into executive narratives and vice versa; strong stakeholder management across CTO, VPs, and ICs
- Experience running programs that span multiple scrum teams, including offshore-heavy organizations
- Hands-on with program/project tooling (Jira, Confluence, or equivalents) and familiarity with engineering metrics (DORA, SPACE, or similar frameworks)
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