Technology Consultant

Endgame; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive salary + bonus

Equity where applicable

Up to 22 days PTO; holidays

Learning budget

Fully remote from EU/UK/US; occasional

Extensive AI tooling

Job summary

Endgame is a premier AI-native consulting and product development firm. You will lead engagements, identify where AI delivers real value in product and engineering, and size the opportunity.

You set targets, prove concepts in weeks, and scale what works, from the terminal to the boardroom. You will work with CTOs, VPs of Engineering, and product leaders to understand systems, diagnose root causes, and recommend changes aligned with constraints and budgets.

Qualifications

• Eight+ years in software with production engineering experience.
• Architecture depth across distributed systems, data, integration, performance, reliability.
• Track record of AI/ML integration in real products: evals, latency, cost, versioning, safety.
• Run discovery workshops and executive/stakeholder interviews.
• Structure ambiguous problems into clear decisions.
• Prepare board-ready artifacts: investment cases, roadmaps, architecture records.
• Technical due diligence: gap analysis and risk mapping.
• Commercial judgment on scope, timeline, margin, buy-vs-build.
• Diagnose engineering delivery problems and separate root causes.
• Explain technical trade-offs to executives and business constraints to engineers.
• Hands-on coding—ship, not just review.
• Move from boardroom to terminal in the same day.

Responsibilities

• Lead consulting engagements from inception to delivery, sizing opportunities and building proofs.
• Quantify ROI and cost of delay, and defend investment cases to executives.
• Diagnose architecture, practices, and foundations; identify blockers to delivery.
• Drive architectural changes to improve scalability, reliability, and velocity.
• Build proofs-of-concept, spikes, and reference implementations; test assumptions.
• Turn validated pilots into production systems with evidence of AI in real workflows.
• Improve delivery flow with targeted process adjustments and accountability.
• Advise engineers and leaders, communicating trade-offs and long-term implications clearly.

Skills

8+ years in software

Architecture depth

AI/ML integration

Discovery workshops

Problem framing

Board-ready artifacts

Technical due diligence

Commercial judgment

Delivery diagnosis

Explain trade-offs

Hands-on coding

Boardroom to terminal

Tools

Architecture reviews

Value-stream analysis

Azure OpenAI

AWS Bedrock

Cloud platforms

Job description

About ENDGAME

ENDGAME is an AI-native consulting and product development firm. Small, senior teams amplified by purpose-built AI tooling deliver strategy and execution in the same hands at software-company economics. We help companies find where AI brings real value, prove it works, and scale the results across the organization.

The Role

You'll lead consulting engagements. You find where AI pays off in product and engineering, size the opportunity, prove it in weeks, and scale what works.

This role runs from the terminal to the boardroom. You write code, build spikes, and read production systems. You also stand in front of executives and make the case, whether you have sixty seconds in an elevator or sixty minutes with the board.

You'll work directly with CTOs, VPs of Engineering, and product leaders. You learn their systems and their delivery, separate symptoms from root causes, and recommend changes that fit their constraints and their budget.

What You'll Do

• Find opportunities: Map the client's product and engineering surface. Spot where AI delivers real gains in revenue, cost, risk, or delivery speed. Cut the ideas that won't survive contact with production.
• Size and justify: Quantify the opportunity. Draft the investment case: cost, time, payback, risk. Set honest targets executives can defend to the board.
• Diagnose systems and delivery: Assess architecture, engineering practices, and technical foundations. Identify where technology or process choices block effective delivery. Distinguish symptoms from root causes.
• Lead architectural change: Identify constraints that limit scalability, reliability, or delivery speed. Drive and validate the architectural changes required to remove them.
• Prove it: Build proofs-of-concept, technical spikes, and reference implementations. Step into code to test assumptions, remove uncertainty, and unblock progress.
• Scale what works: Turn validated pilots into production systems. Produce evidence of AI working in real product and engineering workflows, not in demos.
• Improve delivery flow: Introduce targeted process adjustments that support the technical change. Improve engineering flow, ownership, and reliability. Keep it pragmatic and outcome-driven.
• Advise the room: Work directly with engineers and technical leaders to adopt new approaches. Communicate trade-offs, risks, and long‑term implications clearly. Act as a trusted technical advisor during high‑impact change.

Tools & Methods

• Diagnostics: Architecture analysis, System reviews, delivery audits, value-stream analysis, architecture decision records
• AI/ML: LLM integration, evals, retrieval, agentic systems, Azure OpenAI, AWS Bedrock, custom deployments
• Cloud: AWS, Azure, GCP; preference for serverless/edge (Cloudflare Workers, Durable Objects)
• Business case: Opportunity sizing, ROI modeling, cost‑of‑delay, build‑vs‑buy analysis
• Collaboration: Client workshops, executive briefings, hands‑on pairing with engineering teams

Required Skills

• 8+ years in software, including production engineering experience
• Architecture depth: distributed systems, data, integration, performance, reliability
• Track record of AI/ML integration in real products: evals, latency, cost, versioning, safety
• Run discovery workshops and stakeholder interviews with executives and engineers
• Structure ambiguous problems and reduce them to a short list of clear decisions
• Write board‑ready artifacts: investment cases, roadmaps, architecture decision records
• Technical due diligence: current‑state vs target‑state mapping, gap analysis, risk mapping
• Commercial judgment: scope, timeline, margin, build‑vs‑buy, vendor selection
• Diagnose engineering delivery problems and separate symptoms from root causes
• Explain technical trade‑offs to executives and business constraints to engineers
• Current coding skills, you ship, not just review
• Move from boardroom to terminal in the same day

Nice to Have

• Prior consulting or advisory experience
• Regulated industry experience (healthcare, finance, government)
• Experience scaling pilots into production inside large enterprises
• Cost management skills: cloud spend, total cost of ownership, unit economics
• Developer productivity or platform engineering background

Perks and Benefits

• Competitive salary + bonus; equity where applicable.
• Up to 22 days PTO; public holidays (location‑based); high‑end laptop + tools; learning budget; extensive AI tooling.
• Fully remote from the EU, the UK or the US, with occasional travel.

The Process

1. Getting to know each other (30m)
2. Technical discussion (45m)
3. Case session: diagnose a client situation, size the opportunity, propose a path (60–90m)
4. Offer

FAQ

• Remote? Yes, fully remote from anywhere in the EU, the UK or the US.
• Visa? Case by case.
• AI tools? Extensively.
• Work‑life? Work hard. Rest well. No weekends unless prod is on fire.
• Growth path? Lead engagements Shape the consulting practice Shape the company.
• Who shouldn't apply? Those who prefer slideware to shipped code, avoid hard cost conversations, or need committee approval before deciding.

Equal Opportunity

We're an equal opportunity employer. We evaluate only on the ability to ship real outcomes for clients.