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About us At Cambridge Consultants, we believe the future of technology isn't just smart, it has agency. We're moving past passive tools and building human-centred digital services and products: systems that reason, plan, and act around the people who use them. Our work spans autonomous systems at the frontier of biology, sensing, and AI. We hire self-motivated builders, not ticket-takers. If you thrive in highly agile environments, can cut through ambiguity with first-principles thinking, and want to ship things that matter, this is the kind of place where you'll feel at home. About the role You'll be working on systems that haven't existed before. Think of an Agentic Coach that navigates the unpredictability of human biology, or the software architecture behind a fully automated Dark Lab. These aren't chatbots waiting for questions. They're proactive systems that maintain world models, interpret human intent, and intervene before the user knows to ask. These systems create genuine impact for clients tackling problems no one else can solve. Building them means designing and wiring agent harnesses: layered architectures that span from sensor-edge reasoning to high-level planning, backed by stateful multi-turn reasoning, persistent per-user memory, and robust evaluation pipelines. You'll work in two directions at once. Internally, you'll use the latest AI tools to sharpen how we build, prototype, and ship. Externally, you'll deliver the breakthrough systems our clients deploy, designed to move from prototype to production at pace. There's no single technology stack. You'll work with agents, multi-agent systems, and the latest generative AI tools, but your work will always be grounded in solid software engineering. Expect to build scalable distributed systems in core languages like Python and TypeScript, leveraging frameworks such as NextJS and Pydantic, agent orchestration tools (LangGraph, CrewAI), and protocols like MCP. You'll deploy on cloud platforms (AWS, GCP, Azure) using Docker, Kubernetes, and infrastructure-as-code, backed by rigorous CI/CD and observability (OpenTelemetry, Prometheus). Due to the clients we work with, you must be eligible for UK security clearance. What we ask of you The examples below describe the core domains our AI Engineers own within the Digital Services team. We don't expect every candidate to have mastered all of these, but if you can demonstrate a strong combination of the following, we'd love to hear from you. AI System Architecture: Designing and implementing the logic for autonomous systems, including maintaining world models, integrating multimodal sensing, and building real-time human-machine interaction loops. Infrastructure & Production Engineering: Designing the underlying software for scalable, secure, and observable cloud deployments. You will apply the engineering rigor required to take experimental AI from concept to robust live launch. Rapid Client Prototyping: Driving a demo-first delivery model. You will focus on fast experimentation to actively show tangible value and working software to clients, rather than describing it in slide decks. Domain Translation & Integration: Partnering directly with deep-tech subject matter experts (like biologists and roboticists) to apply software solutions to complex physical constraints. Indicators you'll be a good fit Applied AI Expertise: You have hands-on experience utilising multi-agent frameworks, long-term memory systems, RAG pipelines, vector/graph databases, and reasoning-loop patterns (such as ReAct and Chain-of-Thought). Core Software Fluency: You possess strong programming skills in Python and TypeScript, coupled with practical experience in cloud engineering, containerisation, and modern DevOps. You know that great agents still require rock-solid software foundations. High Tolerance for Ambiguity: You are energised by uncertainty and shifting targets. You treat changing requirements as a normal part of frontier work, and you know exactly when to ship a rough prototype to learn quickly versus when to slow down for architectural rigour. Cross-Disciplinary Communication: You can seamlessly navigate the gap between code and reality, collaborating with clients, roboticists, and scientists to clearly deliver the "art of the possible." Benefits Variety of work: Projects spanning biotech, finance, robotics, and beyond. No two engagements look alike. Continuous learning: A mentoring and learning package shaped by your goals, backed by squad-based knowledge sharing across the company. Engineering autonomy: A free hand in choosing the right tools and processes. We trust your engineering judgement. Access to world-class experts: You'll share a building with biologists, roboticists, electronics engineers, and mathematicians. Few places let you tap that range of expertise on a single project. Hybrid working environment: We're flexible about where you work on a day-to-day basis. We also love the energy of collaborating in person, so we’d love you to be in Cambridge for key meetings. By submitting an application to Cambridge Consultants, you confirm that the information provided in this application, together with any supporting documentation, is true, complete, and accurate to the best of your knowledge and belief. You understand that any false statement, misleading information, or material omission may render you liable to disqualification from the recruitment process, withdrawal of any offer of employment, or dismissal without notice if discovered following appointment. You acknowledge that the organisation reserves the right to verify the information supplied.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.