SeniorLead Quality Engineer Chatbot

Mimica is an AI-powered process intelligence platform enabling enterprises and individuals to reclaim their most precious resource: time. Weve all seen repetitive tasks and redundant processes quietly drain productivity and creativity. Not because companies dont want to become more efficient but because they dont know where to start.

At the click of a button Mimica identifies every process improvement and agentic AI opportunity across an enterprise. Our software turns everyday work into data-backed decisions helping companies remove process bottlenecks automate the right tasks and upskill teams with precision and confidence.

Weve raised $26 million in Series B financing and are scaling fast. Backed by investors including Khosla Ventures and Paladin Capital our proprietary AI technology is trusted by Fortune 500 companies to accelerate transformation. Mimica is recognized as a Top 100 AI Start-up by Accel and an industry Leader by the Everest Group.

Behind our platform is a team of exceptionally talented people remote-first and globally distributed across 16 countries. Were looking for curious collaborative people excited to solve complex problems. Youll join a fast-paced environment built on high ownership bottom-up thinking and transparent open communication helping some of the worlds leading organizations transform the way work gets done with AI.

We are looking for a Quality Engineer to help us build a faster and more reliable testing and release processes for one of our latest product engineering teams. You will work closely with Software and Machine Learning Engineers to establish the quality foundations for a product characterised by dynamic non-deterministic outputs.

The team is a newly formed multidisciplinary team of 5 responsible for the conversational AI components across our Web App. As the teams founding Quality Engineer you will play a central role in defining how we approach quality from the outset. You will introduce thoughtful pragmatic practices that increase confidence in releases reduce remediation and rollback work and enable the team to move quickly without compromising user trust or product reliability.

You will have meaningful ownership from day one: exploring testing approaches identifying quality gaps and helping shape the systems and processes that support sustainable delivery. This is an opportunity for someone who thrives in ambiguity combines hands-on technical testing with experimentation and wants to define quality engineering at the intersection of software development and LLM-powered products.

• Develop and evolve quality practices test strategy and release processes for the Chatbot product.

• Help establish and run an output-evaluation framework for assessing Chatbot quality reliability and regressions.

• Test dynamic and non-deterministic LLM-based systems designing pragmatic approaches for validating behaviour beyond conventional deterministic test cases.

• Identify test and improve guardrails for AI-specific risks including prompt-injection scenarios and unsafe or unexpected model behaviour.

• Partner with engineers through code reviews technical discussions and collaborative debugging to improve quality earlier in the development lifecycle.

• Investigate current testing gaps research relevant methods and tools and make evidence-based recommendations to the team.

• Design proof-of-concepts for new testing approaches or tooling then help product ionise the solutions that create the most value.

• Support the evolution of release testing including clearer quality signals and release-readiness criteria.

• Contribute performance-testing thinking for LLM-powered workflows where relevant.

• Share knowledge facilitate technical discussions and build the Quality Chapter across the wider engineering organisation.

• Strong hands-on experience in software quality engineering SDET test automation or a closely related engineering role.

• Experience testing chatbot conversational AI RAG LLM-powered or other systems with dynamic and non-deterministic behaviour; even early practical exposure is valuable.

• Proficiency in at least one programming language and enough technical depth to understand production code contribute to code reviews and collaborate effectively with software engineers.

• An experimental investigative mindset: you can explore an uncertain problem space assess alternatives and turn findings into practical improvements.

• Clear written and…