Infinite Lambda is Europe’s fastest-growing data and AI consultancy. We empower leading companies to scale and become data-first through agile, cloud-native solutions and cutting-edge practices.
Our mission is to bring top professionals together to make an impact at the intersection of tech and sustainable growth.
Headquartered in London and having distributed teams based in the UK, France, Hungary, Slovakia, Bulgaria, Vietnam, Singapore, Italy, Romania and now expanding to South America we embrace diversity and make sure everyone is happy to be their true self at work. We have already started building teams in Brazil, Argentina, and Chile, and are looking forward to welcoming more teammates to contribute to meaningful projects. Together, we can grow, learn, and experiment with the cutting-edge data and AI technology (dbt and Snowflake among others) that we are all excited about.
We are looking for a high-trajectory Associate Product Engineer to join our team supporting a high-impact product. This isn't your traditional developer role. You will be building across the entire stack while pioneering agentic workflows using cutting-edge AI agents as your default implementation tool, while maintaining strict, ultimate human ownership over the code you ship.
A core pillar of this role is becoming a modernisation specialist. You will build deep domain expertise in how legacy systems (Informatica, SSIS, Talend, IICS) map onto modern data stacks (dbt, Fivetran, and cloud data warehouses).
Implements across the stack: backend, frontend, the IDE extension, and conversion logic, in Python or whichever languages we adopt. Goes where the work is across the stack.
Ships features against the spec using agents as the default implementation tool, and writes the spec themselves for simpler, well-bounded features (with Cristiano's review).
Becomes a modernisation specialist: deep working knowledge of how Informatica, SSIS, Talend and IICS objects map onto dbt, Fivetran and the warehouse. This is the domain expertise the role is built around.
Demonstrates real, working understanding of the code they merge. Reads it, challenges it, and can explain every line. Catches plausible-but-wrong output, hallucinated APIs, and drift from spec, so the agent never takes them for a ride.
Writes failing tests from the spec's acceptance criteria first. No test, no PR.
Logs every agent failure mode into the team's prompt and skill backlog. This is how the team compounds.
Throughput: agreed feature/slice count per fortnight, scoped with the CPO, rising as autonomy grows.
Spec adherence: % of PRs matching acceptance criteria without rework. Target at least 90% after three months.
Change failure rate on merged PRs, measured at UAT and in production.
Code comprehension: in review, can explain and defend their merged code. Agent-driven errors that reach review fall over time. This is the signal that they are in control of the agent's output.
Modernisation depth: by month 12, the go-to person on the team for at least one source-vendor mapping pattern.
Growth gate (12 months): authors a small subsystem spec end to end, signed off by Founding Architect.
This is an exciting role that requires an impressive tech stack along with an amazing personality to thrive in our dynamic and diverse environment.
Experience: 1 to 5 years of software engineering experience, or a strong portfolio of self-directed projects. We hire for aptitude and trajectory at this level, not a long track record.
Agentic tooling: Day-to-day use of at least one agentic coding tool (Claude Code, Cursor, or equivalent), not occasional use. Comfortable working in a governed codebase where agents open pull requests under guardrails and a human reviews.
Engineering: Able to write and read code across the stack, primarily in Python, including frontend work and an IDE extension. Able to explain every line of code you merge, including code an agent wrote. Writes tests from acceptance criteria.
Data fundamentals: SQL and a working grasp of data transformation concepts. Exposure to dbt, Fivetran, Snowflake, or Databricks is useful but not required.
Judgement: Demonstrated ability to catch wrong agent output. A specific example of an agent failure you found and corrected is required at interview.
Education: A degree in Computer Science, Engineering, or a related field is preferred, or equivalent practical experience.
The following soft skills are highly appreciated:
You are a self-starter and don’t need someone to tell you what to do all the time
You are comfortable working in a distributed team
You take pride in your work
We support your growth with dedicated learning time, access to top-notch resources and a knowledge-sharing culture;
You work autonomously here in a wholesome environment and get as much paid holiday as you need;
The projects are diverse and give you plenty of opportunity to experiment with new tech;
The benefits are plenty, with work-from-home budget, a company MacBook and more on the list.
▶ ▶ Submit your CV in English in PDF.
▶ ▶ Mind that as we are an international team, internal communication is in English.
▶ ▶ To ensure legislative compliance, applicants may be asked to provide up-to-date proof of a clean criminal record. Examples of said proof include extract n°3 of the Criminal Record (France), Büntetlen előélet (Hungary), Disclosure and Barring Service (DBS) check (UK), an extract from the Criminal Register (Slovakia), or a country-specific equivalent. Providing proof of a clean criminal record is the final step in the hiring process and will only be requested should the applicant accept an offer from Infinite Lambda.
Infinite Lambda is an equal opportunity employer. Our inclusive culture celebrates diversity and treats everyone with dignity and respect. Accordingly, our selection process will never discriminate against applicants on the grounds of any characteristics, such as disability, age, gender, sexual orientation, family status, race, faith or other.
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