Sr. Technical Project Manager (TPM) at Qode

, , United States -

Full Time

Start Date

Immediate

Expiry Date

05 Oct, 26

Salary

0.0

Posted On

07 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Technical Program Management, AI/ML Delivery, SDLC Modernization, Stakeholder Management, Agile Methodologies, Jira, Confluence, Risk Management, Project Planning, Engineering Metrics, Cross-functional Leadership, Agentic Architecture, Test Automation, Observability, Capacity Planning, Process Improvement

Industry

Software Development

Description

About the Role: We’re looking for a Sr. Technical Project Manager (TPM) to drive delivery for complex, cross-functional initiatives—including those involving AI/ML and intelligent automation. You’ll balance scope, timeline, and dependencies while partnering across Engineering, Product, Data, Security, and Operations to deliver high-quality outcomes. This role is ideal for someone who can run tight execution rhythms and understand the unique delivery needs of AI work (experimentation, data readiness, evaluation, governance, and iteration) in the rollout of the AI-Driven SDLC (AIDLC), What You’ll Do: 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. What We’re Looking For (Required Qualifications): 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). What Success Looks Like (First 90 Days) Delivery plans are clear, realistic, and transparent; stakeholders consistently know status, risks, and next steps. Dependencies are surfaced early and managed actively; team execution rhythms are consistent and effective. AI-related initiatives have strong delivery hygiene (milestones, measurable outcomes, and aligned execution across data/Product/Engineering). Why This Role You’ll play a pivotal role in delivering cross-functional technology initiatives—and help the organization execute confidently as AI becomes a more central part of products and operations. You’ll bring clarity, momentum, and structure to complex work while partnering with leaders across Engineering, Product, and Data.

Responsibilities

Drive the delivery of complex, cross-functional AI/ML initiatives and the rollout of an AI-Driven SDLC. Lead project execution by managing timelines, risks, and dependencies while partnering with Engineering, Product, and Data teams.