AI Software Engineer - The Factory

Avvoka

Praha
Smlouva
Plný úvazek

Před 2 měsíci

We’re AvvokaWe build drafting technology that's transforming the way the world contracts - our platform helps legal teams move faster through contracts using automation and AI, without taking judgement away from the lawyers in control. We believe technology should amplify expertise, not replace it.Avvoka is trusted by over 20% of the AmLaw 100 law firms, global banks and enterprises, and we've grown largely through product strength. With headcount and revenue contuining to scale rapidly year on year, we're now moving from a product-led path into a globally recognised legal-tech brand.We're at an inflection point: evolving how the world's most sophisticated legal teams work — and building a company where thoughtful people can do the best work of their careers.Why join usThis isn’t “add an AI chatbot to the product.” You’ll be building the system that builds the software.We’re building The Factory: an agentic system that turns GitLab issues into production-ready merge requests — automatically. Think multi-agent pipelines, LLM orchestration, and developer tooling that actually ships code. The work is hands-on and high-leverage: if The Factory gets better, Avvoka ships better and faster across the board.You’ll work directly with the team lead on architecture and approach, with real autonomy to shape how AI-powered development works inside a legal tech startup. You’ll also be close to a team that cares about reliability and trust: in legal workflows, “almost right” isn’t good enough — so the engineering craft (evaluation, guardrails, observability) matters as much as the model capability.Role details

Department: Engineering (AI platform / developer productivity)
Engagement focus: Individual contributor delivery (contract)
Primary point of contact: Engineering Lead (The Factory)
Location: Prague Hybrid (3 days a week in office)
Billable hours: up to 160 a month
Compensation: Competitive, based on experience
Start date: As soon as possible

What you’ll doBuild and extend The Factory

Build and extend The Factory, our multi-agent system that processes GitLab issues end-to-end through specialised agents.
Ship production-grade workflows that move from issue → plan → code → review → merge request.
Iterate quickly while keeping quality high through strong interfaces, tests, and system design.

Orchestrate agentic workflows that are reliable

Design robust agentic workflows using tools like BAML, MCP, and DSPy (or equivalents).
Build guardrails that keep outputs predictable: structured outputs, tool/function calling patterns, retries, and fallbacks.
Ensure workflows degrade gracefully when context is missing, requirements are ambiguous, or models behave unexpectedly.

Write the glue between LLMs and real codebases

Implement context retrieval across repos: ownership boundaries, relevant files, conventions, and dependencies.
Build code generation and automated review loops that respect architecture and patterns in the codebase.
Create merge request creation flows (branching, commit hygiene, CI awareness, and reviewer-friendly diffs).

Stay AI-native and keep us ahead

Work daily with AI-native dev tools: Claude Code, Codex, Gemini CLI, and whatever drops next week.
Continuously evaluate new AI development tools and decide what’s worth integrating (and what isn’t).
Improve developer experience: faster cycles, fewer regressions, better signals for humans reviewing AI-generated changes.

What success looks likeTo ensure your application has the best opportunity of success, your CV could cover the below measures of success with quantifiable results (e.g. percentages, growth, reductions, impact)

Increased “issue → merge request” throughput (e.g. reduced cycle time, increased weekly shipped PRs/MRs, improved lead time).
Improved quality and reliability of agent output (e.g. higher pass rate on eval suites, fewer CI failures, fewer reviewer-requested rewrites).
Reduced engineering overhead (e.g. fewer manual steps, fewer repeated fixes, lower rework rate, improved developer satisfaction signals).

What you’ll bring

You’ve actually built with AI coding/agent tools in real workflows (not just demoed them).
Strong TypeScript and/or Python (bonus if you’ve worked with Ruby on Rails).
Comfort with prompt design, agent orchestration patterns, and basic LLM evaluation (offline and/or in-product signals).
You understand software architecture well enough to teach an agent about it: boundaries, trade-offs, conventions, and what “good” looks like in a real codebase.

Hard requirement (the only one): hands-on experience with at least one AI-native dev/agent tool (e.g. Claude Code, Codex, Gemini CLI, or similar). If you’ve used one deeply, we can help you ramp on the rest.Bonus points if

You’ve built multi-agent pipelines that coordinate planning, coding, review, and integration.
You’ve implemented retrieval and context-building for large repos (ownership, dependencies, patterns).
You’ve built eval harnesses (golden sets, regression checks, rubric scoring, or CI-integrated gates).

If you’re excited about this role but your experience doesn’t align perfectly with every item above — or you haven’t used all the technologies mentioned — we encourage you to apply anyway. We care most about strong fundamentals, curiosity, and evidence you can ship.Core attributes we value across all rolesAdaptability in dynamically evolving settings
A proactive, solution-focused mindset with ownership
A collaborative spirit, supporting and mentoring othersIf you’re excited about this role but your experience doesn’t align perfectly with every qualification, we encourage you to apply anyway — you might be just the candidate we’re looking for.Our hiring process

CV review – We review your CV for evidence of role alignment, impact, and ownership.
Screening call – A short call to understand your background, motivations, and what you’re looking for next.
Assessment interview – A practical session focused on how you approach problems relevant to the role.
Senior interview – A deeper conversation on technical judgement, collaboration, and role fit.
Meet the team – Time with future teammates to ensure mutual fit and answer your questions.

What we offer

Clear scope of work, with clear success criteria and meaningful deliverables
Ability to invoice via own company / umbrella / sole trader
Autonomy over how and when work is delivered
Access to necessary systems, tools, and documentation
Clear success criteria and delivery milestones
Opportunity to work on complex, high-impact problems
Exposure to enterprise / scale-up environments
Ability to shape systems, processes, or architecture
Strong portfolio / reference value

Equal opportunitiesWe’re committed to building an inclusive workplace where everyone feels respected, valued, and able to do their best work. We welcome applications from all backgrounds and do not discriminate on the basis of race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or any other protected characteristic.Avvoka

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