Technical Project Manager

Lead end-to-end delivery (B2B & B2G) AI and dashboard products—turning stakeholder needs into clear requirements, driving execution across engineering/DevOps/data teams, and staying hands-on enough to validate quality and shape solution design. You’ll operate in regulated environments with strict security, data residency, and governance requirements.

B2G/B2B stakeholder leadership

• Own delivery across government stakeholders (executives, operations, IT/security, data owners, procurement/legal, external vendors).
• Run discovery workshops; document business processes, user journeys, and success metrics.
• Translate requirements into epics/stories, acceptance criteria, rollout plans, and UAT plans.
• Manage change requests, approvals, and procurement constraints while protecting scope/timeline outcomes.
• Produce B2G/B2B-ready artifacts: MoM, RAID log, implementation plan, SOP/runbooks, training materials, and governance documentation.

Solution shaping (technical + product)

• Partner with engineering/data/AI teams to define the solution approach and delivery architecture:
• Data ingestion and integration from multiple systems (APIs, files, DBs, event streams)
• Data modeling, metadata, and access controls for cross-division reporting
• AI/LLM features (summarization, classification, RAG, NLQ-to-SQL) with safety/guardrails
• Dashboard analytics (KPIs, drill-downs, auditability, role-based views)
• Define and manage non-functional requirements: security, audit logs, availability, DR, performance, retention, observability.
• Drive interface contracts: API specs, event schemas, data contracts, permission model.

Hands-on validation & quality ownership

• Build test strategy: functional, integration, performance, security checks, and UAT.
• Write/maintain acceptance criteria and test cases; execute smoke/regression tests per release.
• Validate end-to-end user flows across integrations, identity, data pipelines, AI outputs, and dashboards.
• Lead release readiness: deployment checklist, rollback plan, monitoring verification, DR/backup validation.
• Triage issues with clear severity/impact and prioritization; coordinate fixes and stakeholder comms.

Delivery operations & governance

• Run agile delivery (planning, grooming, daily sync, demos, retros); maintain delivery dashboards and reporting.
• Own release management and go-live planning (pilot → phased rollout → scale).
• Maintain a single source of truth: PRD/BRD, backlog, decision log, and change log.

Required qualifications

• 5+ years delivering software/data platform projects, plus value in B2G/regulatory environments.
• Strong requirements engineering: discovery, process mapping, writing BRD/PRD, measurable acceptance criteria.
• Proven delivery leadership across cross-functional teams (engineering, data, AI/ML, DevOps, security).
• Comfortable in complex stakeholder environments with approvals, audits, and vendor dependencies.
• Able to communicate clearly at exec level and at technical detail level.

Technical skills (practical level)

• APIs & integration: REST, webhooks, authentication basics (OAuth/OIDC), event-driven concepts.
• Data fundamentals: SQL basics, data quality concepts, pipeline validation, KPI definitions.
• AI/LLM product literacy: prompt-based workflows, evaluation basics, hallucination risk, guardrails, feedback loops.
• Infra design fundamentals: Linux basics, containers, deployment concepts, monitoring/logging, incident management basics. Understanding of server and GPU specs.
• Security fundamentals: RBAC, least privilege, secrets handling, audit trails, data classification and residency.
• Git/Github

Nice-to-have

• Experience delivering analytics/dashboard platforms (BI, custom dashboards, KPI frameworks).
• Experience with AI governance: model evaluation, human-in-the-loop review, prompt/version control.
• Experience with on-prem/hybrid deployments, DR planning, and regulated data environments.
• Familiar with government procurement/vendor management and compliance documentation.

Success metrics

• Requirements baseline agreed with traceability to KPIs and acceptance criteria.
• Predictable release cadence with high-quality UAT outcomes and clear rollout readiness.
• Production stability: monitoring/runbooks in place, incidents handled with strong RCA and prevention.
• Stakeholder trust: clear reporting, controlled scope, and measurable delivered outcomes.

• Base fee/salary (per contract or employment agreement).
• Project completion fee (success fee): paid upon successful completion and formal acceptance of agreed deliverables (e.g., MVP/phase acceptance sign-off), subject to meeting defined SLAs/UAT criteria and documentation/runbook handover.