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Forward Deployed Engineer We are looking for a Forward Deployed Engineer to join our Team and work directly with operating companies across the Group to turn real-world operational challenges into deployed AI solutions. This is a hands-on engineering role for someone who enjoys working closely with business users, understanding how work is performed, building practical AI solutions and taking them all the way from discovery to production and handover. The successful candidate will combine software engineering, AI/LLM development, systems integration and business problem-solving to deliver solutions that create measurable operational value. Key Responsibilities Work directly with operating companies to identify operational problems and translate them into practical AI and automation solutions. Conduct process discovery, requirements gathering and stakeholder interviews. Design, build, test and deploy AI-powered solutions using internal platforms, models and reusable components. Develop solutions using Python, LLM APIs, RAG, vector databases, agent frameworks and workflow orchestration . Integrate AI solutions with existing operational systems, APIs, data sources and business workflows. Rapidly prototype solutions, test them with real users and iterate towards production-ready implementations. Develop evaluation and testing frameworks to measure AI solution quality and performance. Monitor deployed solutions in production and troubleshoot performance, quality and integration issues. Work with Group IT, Information Security, Data & Analytics and business teams to ensure appropriate architecture, security and compliance. Document solutions and prepare technical handover materials. Train business users and operational owners to use, maintain and extend deployed solutions. Track and report measurable benefits from each deployment, including cost savings, productivity improvements and licence displacement. Identify reusable components and patterns that can accelerate future AI deployments across the Group. Support build-versus-buy assessments by demonstrating the technical feasibility and total cost of internally developed solutions. Where required, lead temporary delivery pods or coordinate the work of interns. Requirements Bachelor's degree in Artificial Intelligence, Computer Science, Software Engineering, Data Science, Industrial Engineering or a related discipline . 1–3 years of hands-on experience building and deploying software or AI solutions into production. Proven experience delivering solutions used by real users beyond proof-of-concept or experimental environments. Recent practical experience developing applications using Large Language Models (LLMs) is required. Strong experience with Python for application development and/or data-related work. Experience working with LLM APIs, prompt engineering and context design . Practical knowledge of Retrieval-Augmented Generation (RAG) and vector databases. Experience with AI agent frameworks and workflow orchestration . Experience with APIs, system integration, SQL and data pipelines . Exposure to AI evaluation and testing frameworks. Experience with cloud platforms and deploying/managing applications in cloud environments. Exposure to lightweight front-end development for internal tools is an advantage. Strong process mapping, business analysis and requirements-gathering skills. Ability to communicate technical concepts to non-technical stakeholders. Experience working directly with clients, business units or operational teams is strongly preferred. Exposure to logistics, supply chain or operations-heavy environments is an advantage. Key Technical Skills Python | Generative AI | LLMs | LLM APIs | Prompt Engineering | RAG | Vector Databases | AI Agents | Workflow Orchestration | API Integration | SQL | Data Pipelines | AI Evaluation | Cloud Deployment | Software Development | Process Automation What We Are Looking For We are looking for an engineer who is comfortable operating at the intersection of technology and business . You should be able to take an ambiguous operational problem, understand it directly from users, design a technical solution, build it, deploy it into production and ensure that the business can successfully use and maintain it. Candidates whose experience is limited to academic projects, training or POCs without production deployment experience will not be considered.
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.