Parser
Forward Deployed Engineer

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Forward Deployed 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?
As a Senior Forward Deployed Engineer, you will build and ship AI-powered products directly alongside senior investment professionals, portfolio leaders, and corporate teams, solving complex, high-stakes financial challenges through technology.
This is a deliberately broad and hands-on role. You will move fluently across frontend, backend, data, cloud infrastructure, and applied AI, owning solutions end-to-end, from a whiteboard session with a deal or risk team, through rapid prototyping and validation, to a secure, scalable, enterprise-grade service running in production.
Being forward deployed means spending significant time embedded with the people who use what you build across investment, portfolio management, risk, finance, and legal. You will translate ambiguous business problems into working software in days and weeks, continuously iterate based on real-world feedback, and evolve solutions that prove their value into durable capabilities across the wider platform.
Your key responsibilities:
- Embed directly within investment, portfolio, risk, and corporate teams to understand workflows and decision points, translating ambiguous business problems into functional software solutions.
- Lead rapid discovery and prototyping cycles, using strong hands-on coding and AI-assisted development to deliver working software early and continuously iterate based on user feedback.
- Own end-to-end production vertical slices, including data ingestion and modelling, backend services and APIs, AI orchestration, frontend experiences, deployment, and operations.
- Design and build production-grade AI features, including RAG across structured and unstructured investment data, agentic workflows, document intelligence, and AI-generated analytics.
- Build intuitive, information-dense interfaces for investment professionals, including analytical grids, complex data visualisations, and human-in-the-loop review flows.
- Deploy and operate workloads across Kubernetes (AKS) and Azure PaaS, using infrastructure as code, automated CI/CD, and instrumentation across logging, tracing, evaluation, observability, and cost.
- Apply enterprise-level security, entitlement, data governance, and audit standards appropriate for a regulated and highly confidential investment environment.
- Champion engineering excellence across testing, architecture, design patterns, and responsible AI evaluation, while mentoring and supporting other engineers.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What you’ll bring to the role:
Essential Requirements
- 8+ years of software engineering experience, with a track record of shipping production-grade systems and strong architecture, testing, and engineering rigour.
- Genuine full-stack expertise across Python, C#, TypeScript/React, advanced SQL, and complex data modelling, working with both structured and unstructured data.
- Proven applied AI/LLM experience, shipping production solutions using RAG, embeddings/vector search, agentic workflows, evaluation frameworks, and guardrails.
- Hands-on cloud and infrastructure expertise across Azure and Kubernetes (AKS), including containerisation, IaC, CI/CD, deployment, and observability.
- Direct investment or financial markets experience across asset management, sovereign wealth, private equity/credit, venture capital, institutional investing, fintech, investment banking, or capital markets technology with knowledge of the investment lifecycle, investment data (IRR/MOIC, NAV, valuations, cap tables), and financial-sector confidentiality, entitlement, audit, and regulatory requirements.
- Outstanding communication, autonomy, and adaptability, with the ability to work directly with senior stakeholders, navigate ambiguity, and deliver effectively under pressure and shifting priorities.


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Desirable Requirements
- Prior forward-deployed, solutions-engineering, or founding-engineer experience within an AI/enterprise software company, high-growth startup, consultancy, or regulated enterprise.
- Experience integrating financial data providers (Bloomberg, LSEG/Refinitiv, FactSet, S&P Capital IQ, PitchBook, Preqin, MSCI), parsing financial documents at scale, and/or optimising LLM performance, cost, and latency.
- Exposure to enterprise data architectures (Kafka/Event Hubs, lakehouse, Snowflake, Oracle) and experience distributed international teams.
Location & Work Model:
London, UK: Hybrid model, requiring 2-3 days per week in the office in Covent Garden.
You will receive:
- The chance to join an organization with triple-digit growth that is changing the paradigm on how software products are built.
- The opportunity to be part of an amazing, multicultural community of tech experts.
- A highly competitive compensation package.
- A flexible and hybrid working environment.
- Private medical insurance.
Parser is committed to fostering an inclusive workplace and providing equal employment opportunities to all applicants regardless of race, religion, gender, sexual orientation, age, disability, or any other protected characteristic under applicable law.
If you require reasonable accommodations during the recruitment process, please let us know and we will work with you to support your participation.
By applying to this role, you acknowledge that your personal data will be processed in accordance with Parser’s Privacy Notice for recruitment purposes.
Parser may use AI-assisted tools during certain stages of the recruitment process to support operational efficiency. Our recruiting teams use AI to streamline note-taking and scheduling. All hiring decisions are made by people, with human review and oversight.
Come and join our #ParserCommunity.
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Jessica, London
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