Technical Program Manager

Overview

Role Summary

Execute

• Own the end-to-end delivery plan for SuperHive, coordinating dependencies, milestones, and integration points.
• Break down the platform roadmap into quarterly delivery plans with clear squad-level objectives, measurable outcomes, and realistic timelines — accounting for the inherent uncertainty in AI/ML feature development.
• Partner with Tech Leads and Product Managers daily: enhance clarity on scope, surface dependencies and risks early from PRDs and technical designs, and keep all the parts together.
• Run the program rhythm: sprint cadences, cross-squad syncs, demo cycles, retrospectives. Keep them lean and useful — no ceremony for ceremony’s sake.
• Manage the critical path. When one squad is blocked waiting on another, you find the path forward — whether that means re-prioritizing, descoping, or pulling in help.

Influence

• Own and drive at least one complex cross-functional program end-to-end: the kind of initiative that touches multiple squads, spans Engineering and Product and leadership, and would not happen without someone holding it together.
• Facilitate technical alignment when squads need to agree on API contracts, data schemas, event formats, or shared infrastructure. You do not decide the architecture — you make sure the right people are in the room and the decision gets made and documented.
• Manage external prototyping and development engagements: charter and scope definition, milestone tracking, integration checkpoints, and acceptance criteria. External partners build features that must integrate cleanly with the platform, and you own that lifecycle.
• Challenge the status quo. If a process is not working, propose a better one. If a timeline is unrealistic, say so with data.

Cultivate

• Contribute to building the TPM function itself: shape ways-of-working rituals, bring new ideas for how the team operates, and represent what the function does across the organization.
• Build visibility into delivery health for engineering leadership — dashboards, weekly updates, or whatever format actually gets read and acted on. Honest, data-informed, no sugar-coating.
• Define and enforce release processes: what needs to be true before a feature ships (tests, security, documentation, observability), without making the process a bottleneck.
• Contribute to our clien’s hiring and branding initiatives for the Engineering function.

Ai And Ml Delivery Awareness

• A significant part of what makes this role different from a generic TPM position is the AI/ML delivery context.
• You will need to:
• Understand the non-linear nature of AI workstreams: evaluation-driven iteration, prompt engineering cycles, model performance plateaus, accuracy improvements that come through data and eval loops rather than just feature completion.
• Work with the Intelligence squad to plan agentic AI delivery in phases — knowing that a multi-agent system is not “done” when the code is written, but when the evaluation benchmarks pass.
• Track AI-specific metrics alongside delivery metrics: model accuracy, latency budgets, token costs, evaluation scores. Recognize when these metrics signal a timeline risk.
• Navigate the tension between “move fast” and “get the AI right” — helping squads make pragmatic trade-offs between shipping and iterating on quality.

Required Qualifications

• 7+ years of experience in Technical Program Management, Engineering Management, or an adjacent role where you coordinated technical delivery across multiple teams in a fast-paced environment.
• At least 2–3 years managing programs that included AI/ML workstreams shipping to production — not research or proof-of-concepts, but products with real users.
• Demonstrated experience coordinating 4+ engineering teams working on a shared platform with real inter-service dependencies.
• **Technical fluency:**
• you can read an architecture diagram, understand an API contract discussion, ask informed questions about database schema choices, and recognize when a timeline estimate is optimistic versus grounded.
• You do not write code, but you speak the language.
• **Startup pace:**
• you have operated in environments where scope changes frequently, teams are small, and you balance speed with quality by making smart trade-offs — not by adding process.
• Strong understanding of modern software delivery: CI/CD, microservices, containerization, cloud infrastructure (AWS preferred).
• Excellent written and verbal communication. You write clear status updates that engineering leadership actually reads. You run efficient meetings. You translate technical complexity into executive-friendly language without losing accuracy.
• Experience managing external vendor or partner engagements with clear deliverables, integration checkpoints, and acceptance criteria.

Preferred Experience

• Direct experience with LLM-powered product delivery: understanding evaluation frameworks, RAG pipeline timelines, prompt iteration cycles, and the operational challenges of running LLM agents in production.
• Familiarity with agentic AI architectures: multi-agent systems, tool-calling patterns, orchestration frameworks (LangGraph, LangChain), and what makes them hard to ship reliably.
• Experience with workflow orchestration tools (Hatchet, Temporal, Airflow) and message brokers (RabbitMQ, Kafka) — understanding how data pipelines are built and where they stall.
• Background in B2B or enterprise platform products with multi-tenancy, role-based access, billing, and compliance requirements.
• Experience setting up the TPM or program management function from scratch — defining the cadences, tools, and reporting that actually work rather than inheriting an existing PMO.
• Familiarity with observability tools (Sentry, Datadog, Signoz) — understanding how production health informs delivery decisions.

Who You Are

• Beyond experience, here are the qualities that matter most in this role:
• **Resourcefulness:**
• you thrive when dropped into a new context and figuring out your own way forward.
• You are comfortable where the playbook is still being written, and you shape the function rather than wait to be handed one.
• **Technical curiosity:**
• you can dive into AI concepts and hold substantive discussions with engineers — critiquing designs, surfacing risks, asking the question that makes a tech lead pause.
• **Ownership:**
• you can point to complex programs that would not have shipped without you.
• Not facilitating — owning.
• **Soft power:**
• you influence without authority, push back without making it personal, and stay credible with engineers, PMs, and leadership at the same time.
• **Clarity:**
• you connect the dots others miss, especially around cross-team dependencies and organizational bottlenecks.
• You reach alignment through shared understanding, clear writing, and consistent direction.