Senior AI Engineer

Senior Artificial Intelligence Engineer
Who is Parser?
Technology alone does not create impact- the right teams do. Founded in 2018, Parser is a boutique technology services and consulting firm helping global organisations solve complex business challenges through digital transformation, product development and AI enablement.
We are a fast-growing team of 340+ engineers and consultants across Europe (UK, Spain, Portugal), the Americas (US, Argentina, Uruguay, Colombia), and the Middle East.
We combine global reach with a mindset focused on agility, senior expertise, and close collaboration. We work as an extension of our clients’ teams, helping them define the right problems, shape solutions, and deliver technology-driven outcomes that create measurable business value. Our expertise spans software engineering, AI & data, product development, and customer experience, delivered by teams that combine strong technical depth with a consulting mindset.
Why Join Us?
If you are looking for a place where you can think beyond execution, take true ownership of outcomes, influence decisions, and continuously learn alongside top-tier specialists in a truly global environment, we’d love to meet you.
How will you impact?
We are looking for technically strong, pragmatic engineers with a primary focus on AI, including hands- on experience with Generative AI and large language models (LLMs).
Candidates should also bring solid software engineering practices and a good data background, enabling them to build, deploy, and operate AI-driven solutions in production. We value engineers who collaborate openly, adapt quickly, and focus on delivering practical, usable outcomes.
Your key responsibilities:
Soft Skills
Collaboration & Ownership with Alignment
Share work early and often, making it visible through docs, demos, and incremental PRs
Own deliverables following team architecture and workflows
Communicate decisions, assumptions, and trade-offs clearly to the team
Avoid working in isolation on critical paths; seek alignment when decisions impact others
Curiosity & Bias to Action
Experiment, validate quickly, and iterate based on frequent stakeholder and team feedback
Suggest improvements grounded in problem-solving rather than tech preference
Balance exploration with delivery, avoiding over-engineering early
Pragmatism & User-Centric Thinking
Optimize for Analytics and Trading adoption, clarity, and trust
Make sensible trade-offs to deliver usable value early, even if the solution isn’t yet “perfect”
Adaptability
Open to feedback and able to adapt as the team and project scale in communication, scope, and technical direction
Hard Skills
Data & Analytics Engineering
Strong SQL and experience working with large analytical datasets
Familiarity with distributed data platforms (e.g., Spark, Trino, Databricks)
Understanding of data modelling, joins, aggregations, and performance trade-offs
MLOps & AI Platform Operations
Experience operationalizing ML and LLM-based systems in production environments
Familiarity with model lifecycle management (training, versioning, deployment, rollback)
Understanding of monitoring and observability for ML systems (performance, drift, data quality)
Experience with automation around pipelines, evaluations, and deployments
Awareness of scalability, reliability, and cost considerations for AI workloads
Hands-on experience with AWS, including designing and operating production-grade cloud infrastructure
Evaluation, Reliability & Safety
Understanding of AI evaluation approaches (offline tests, benchmarks, qualitative review)
Familiarity with logging, monitoring, and debugging AI-driven systems
Awareness of common AI risks (hallucinations, bias, drift) and mitigation strategies
Software Engineering Practices
Strong coding fundamentals and testing discipline
Experience with CI/CD pipelines and production environments
Comfortable working with evolving requirements and iterative delivery
What you'll bring to the role:
Demonstrated +5 years of experience in data engineering and AI/system development in a production environment
Proven ability to ship iterative, user-focused solutions with attention to reliability and safety
Strong communication skills and a collaborative mindset
Nice to Have
Experience in analytics or trading domains
Experience with vector databases, retrieval-augmented generation (RAG), or LM-based tooling in production
Hands-on experience with AWS, including designing and operating production-grad

Employment type
Full-Time

Work arrangement
No