AI Lead / Engineering Manager

Posted 5 Days Ago
27 Locations
Remote
Senior level
Information Technology • Software
The Role
Lead a small engineering team building and shipping AI-powered SaaS features. Set technical direction, establish standards for observability, testing, security, scalable architecture, and AI evaluation, while managing delivery timelines and team development. Remain hands-on by designing and implementing production AI systems using LLMs, embeddings, RAG, vector databases, and related tooling. Partner with Product and leadership on prioritization, architecture, resourcing, and risk management.
Summary Generated by Built In

This role is part of our Usersnap team, one of our growing brands at saas.group.

Profile Overview

Usersnap is building AI-driven capabilities into the core of the product, from automated setup to intelligent surveys, contextual analysis, and reporting that generates itself based on connectors. We're looking for a hands-on AI Lead / Engineering Manager to lead the small engineering team that ships these capabilities, and to set the technical direction while doing it.

This is a player-coach role. You'll write and review code, make architecture calls, and define what "good" looks like for AI-native development. You'll also own team coordination, delivery timelines, workload allocation, and follow-through, so that work planned is work shipped, reliably and at production quality.

This is a full-time, engineering-led role. It is not combined with product management: the technical leadership scope is substantial on its own, and you'll partner with Product rather than absorb it.

AI capability is becoming core to Usersnap's product and go-to-market, especially as we move upmarket. You'll be the person who makes sure it ships well.

Your immediate impact in the first 3-6 months will be:
  • You'll have established a clear delivery rhythm for the team: shared priorities, realistic timelines, visible workload, and projects that get followed through to launch
  • You'll have assessed the current state of the codebase, tooling, and practices, and set out a concrete engineering bar covering observability, testing, security, and architecture
  • You'll have shipped at least one AI-powered feature to production with the team, from prototype through launch, using timeboxed AI development
  • You'll have built a strong working relationship with Product and the rest of the company, and be seen as a reliable owner of ambiguous, technically complex work
  • You'll have raised the team's standards while keeping people motivated and engaged
Your responsibilities

Team leadership and delivery

  • Own team coordination, delivery timelines, workload allocation, and project follow-through for a small engineering team
  • Keep work moving: break down ambiguous goals, sequence them with Product, flag slippage early, and make sure commitments are met
  • Give clear, constructive technical feedback in code review, design discussions, and 1:1s, and raise standards without demotivating people
  • Grow the team's capability, including how we use AI tooling to work faster without lowering quality

Technical leadership

  • Assess the current engineering bar and raise it. Define what "good" looks like for AI-native development, and make it the shared standard
  • Set and enforce expectations in five areas:
    • Observability: logging, monitoring, and tracing that make AI behavior, cost, and failures visible
    • Testing: strong test coverage and automated-testing rigor, including evaluation of AI outputs
    • Security and compliance: secure-by-default practices, as we move upmarket
    • Scalable architecture and data pipelines: designs that hold up as usage and integrations grow
    • Timeboxing: practical limits on AI development work, so exploration stays bounded and ships
  • Own or steward key architecture decisions, including model selection and integration approach, and the tradeoffs between quality, cost, and latency
  • Flag technical risks early, especially around AI reliability, cost, and edge-case behavior

Hands-on contribution

  • Design, build, and ship AI-powered features alongside the team, from prototyping through production quality
  • Work hands-on with LLMs, embeddings, and related AI tooling to solve real product problems
  • Build across the stack as needed. Every feature you ship should be tested, monitored, and maintainable

Partnership

  • Partner with Product on requirements and priorities, pushing back with technical reality when needed
  • Partner with company leadership on technical planning, resourcing, and sequencing
What You bring to the table
  • Leadership

    • Hands-on technical leadership with real engineering vision. You've led delivery for a small team, ideally for 2-3 years of people leadership, as a tech lead, engineering manager, or player-coach. Formal people-management experience is useful, but the essential need is someone who can wrangle delivery and provide senior technical direction
    • A style that raises the bar. You give direct, specific technical feedback and hold high standards, and the team leaves those conversations more capable and more motivated
    • Delivery discipline. You're comfortable owning timelines, allocating work, and following projects through to the end

    Technical depth

    • 7+ years of software engineering experience, and you've shipped AI features to production and owned the lifecycle from problem framing to post-launch iteration, not just prototypes or AI-assisted coding
    • Strong fullstack fundamentals. Comfortable across frontend, backend, and infrastructure as needed
    • Practical experience with LLM APIs, prompt engineering, RAG, or similar techniques in live systems, with good judgment about when AI is the right tool and when it isn't
    • Observability and testing rigor. You build in logging, monitoring, and tracing from the start, and you insist on strong test coverage and automated testing, including evaluation of AI behavior
    • Scalable architecture and data pipelines. Solid SQL, schema design, and the ability to design pipelines and systems that scale
    • Evaluation mindset. You define success metrics, design experiments, run offline and online evaluations, and make decisions from the results
    • Production readiness. Docker fluency, CI/CD, and good habits for versioning prompts, models, and datasets
    • LLM platform breadth. Experience integrating multiple LLM providers, working with vector databases, and using LangChain (or similar); comfortable fine-tuning when it truly makes sense
    • Security and compliance experience, or a strong interest in it, as we move upmarket
    • Practical timeboxing of AI development work. You know how to keep AI exploration bounded, ship on schedule, and avoid open-ended experimentation

    How you work

    • You identify problems and propose solutions on your own, rather than waiting to be told exactly what to build
    • You're comfortable in a lean team where you own outcomes, not just tickets
What's in it for You
  • Ultimate flexibility: We're 100% remote. You can work from wherever you like, whenever you like.
  • Freedom and autonomy: We're a high-trust team, and you'll be given lots of flexibility to solve problems in your own way — with plenty of help from the team when you need it.
  • Minimum bureaucracy: We don't like to get bogged down with meetings and red tape. We like to be efficient and keep momentum steady & sustainable.
  • Small & friendly team: We help each other out, have fun, and joke around.
  • Our network: We are a community of entrepreneurial SaaS professionals that regularly exchange ideas, knowledge, learning and expertise with each other internally.
  • Flexible time off: We want you to recharge your batteries when needed.

Usersnap is part of saas.group and we have a shared goal of succeeding together.

What is saas.group?

Think of us as the driving catalyst behind your favorite software success stories. saas.group, established in 2017, is on a mission to turbocharge promising B2B SaaS ventures, unlocking their full potential. As a Software-as-a-Service portfolio powerhouse, we specialize in acquiring small software treasures and polishing them into industry stars. With a dynamic, fully remote team of nearly 380+ colleagues spanning 50+ countries we are truly global and we are rewriting the playbook on SaaS innovation and collaboration. We grow 25 exciting brands under our umbrella. Feel free to explore our Candidate's Hub to get an insider's view, dive into our culture, gain valuable insights into our teams and how we work.

Also, don’t forget to follow saas.group on LinkedIn to stay up-to-date on our job openings, podcast episodes, and with all things happening at our company.

We don’t just simply offer you to “take a job with us” but rather to “join us on this journey” to build the world's largest platform of independent SaaS companies. 

Sounds like something you’re up for? Feel free to apply even if you don’t check all these boxes. We believe in the power of diversity and fresh perspectives to spice up our team. Your application might just be the missing ingredient!

—

saas.group is committed to creating a diverse and inclusive workplace. We are proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you're passionate about working with a team that values innovation, excellence, and fairness, we encourage you to apply.

We believe in fair and transparent pay. Salary ranges at saas.group are location-adjusted, targeting local market medians for a remote-first environment, and will be shared with our potential future employees in writing before your first interview - so you have everything you need to evaluate the opportunity.

Skills Required

  • 7+ years of software engineering experience
  • Experience shipping AI features to production and owning their lifecycle from problem framing through post-launch iteration
  • Strong full-stack engineering fundamentals across frontend, backend, and infrastructure
  • Practical experience with LLM APIs, prompt engineering, RAG, or similar techniques in live systems
  • Experience with observability, logging, monitoring, tracing, strong test coverage, automated testing, and AI output evaluation
  • Solid SQL, schema design, scalable architecture, and data pipeline design experience
  • Experience defining success metrics, designing experiments, and conducting offline and online evaluations
  • Docker fluency, CI/CD experience, and versioning practices for prompts, models, and datasets
  • Experience integrating multiple LLM providers, vector databases, and LangChain or similar tools
  • Security and compliance experience or strong interest in security and compliance
  • Ability to lead delivery for a small engineering team, coordinate work, allocate workloads, and own timelines
  • Practical experience timeboxing AI development and bounded experimentation
  • 2–3 years of people leadership experience as a tech lead, engineering manager, or player-coach
  • Fine-tuning experience when appropriate
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The Company
HQ: Las Vegas, Nevada
80 Employees
Year Founded: 2018

What We Do

saas.group is a conglomerate of indie businesses founded by experienced industry veterans with proven entrepreneurial, investing, and product backgrounds. We love healthy SaaS companies and help them to reach the next level. If being acquired is something that sparks some interest or you’d like to know about our process, we’d love to have a chat with you. We support all sorts of involvement from investment, founders staying on board to fully taking it off your hands. Learn more about us and our approach on Indiehackers: https://www.indiehackers.com/interview/2f745388db

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