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Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain. We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise — we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions. As Artefact continues to grow globally, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption. The Role Artefact is looking for a Senior AI & Agentic Engineer: a full-stack engineer who takes AI features from idea to production. You will design and build the interfaces, services, and agentic systems at the heart of our client work, such as conversational applications over enterprise data, multi-step agents that automate business workflows, and the retrieval and data pipelines that support them. You will own your components end to end: the React front end, the Python or Node service behind it, the RAG pipeline feeding it, and the evaluations proving it works. This role combines breadth and depth: the ability to take a feature from front end to cloud deployment, together with strong expertise in at least one major AI platform — Google (Gemini), Anthropic (Claude), or OpenAI. You will work with direct client exposure, and you will support the professional development of the junior engineers around you. What You'll Do Build Full-Stack AI Applications, End to End You will build AI products across the entire stack, from interface to infrastructure. Develop user-facing interfaces in TypeScript/React and the backend services and APIs behind them in Python or Node. Implement agentic behavior: orchestration, tool and function calling, memory, and guardrails. Build retrieval-augmented generation (RAG) pipelines: ingestion, chunking, embeddings, vector and hybrid search. Connect AI systems to enterprise data and applications via APIs, semantic layers, and protocols such as MCP. Make AI Systems Production-Grade Our standard is production quality: systems that are reliable, monitored, and maintainable. Write evaluation suites and regression tests for LLM-powered features, and monitor cost, latency, and quality in production. Apply solid engineering practice: version control, code review, automated testing, CI/CD, and observability. Deploy on cloud infrastructure (GCP, Azure, or AWS) using containers, serverless, and infrastructure-as-code. Build and maintain the data pipelines that feed AI systems, across warehouses, lakehouses, and vector stores. Work AI-Natively and Client-Facing Our engineers work AI-natively and represent Artefact directly with clients. Use agentic coding tools (Claude Code, Gemini CLI, Codex, Cursor) daily, with good judgment about verification and review. Communicate progress, trade-offs, and blockers clearly to clients and project leads. Support pre-sales when needed: scope solutions, build demos, and estimate effort with our partnership and consulting teams. Mentor junior engineers and contribute to internal accelerators, reusable components, and engineering standards. What We're Looking For Required Experience 3–5 years of experience in software engineering or data engineering, with extensive hands-on use of AI tools and LLM-based development over the past year (professional projects, internal initiatives, or substantial personal builds). Professional English proficiency mandatory. You will work daily with international clients and colleagues. Strong programming skills in Python and TypeScript/JavaScript, and experience building and consuming APIs. Experience with front-end development (React or similar) and at least one backend framework. Hands-on experience with RAG, embeddings, and vector search, and with at least one agentic framework (LangGraph/LangChain, Google ADK, Claude Agent SDK, or OpenAI Agents SDK). Specialization in at least one major AI platform ecosystem — Google (Gemini, Vertex AI, Gemini Enterprise), Anthropic (Claude, Managed Agents, MCP), or OpenAI (Responses API, AgentKit) — and working experience with one cloud platform (GCP, Azure, or AWS). Fluency with agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor. Experience building and maintaining data pipelines. Bachelor's or Master's degree in computer science, engineering, or a related field, or equivalent practical experience. Certifications A certification on at least one major AI platform or cloud is a strong differentiator at application. If you do not hold one yet, obtaining one within your first 2 months in the role is a requirement — Artefact sponsors the exam and gives you time to prepare. Examples: Claude Certified Developer – Foundations (Anthropic), Google Cloud Professional Machine Learning Engineer, Google Cloud Generative AI Leader, Microsoft Azure AI Engineer Associate, or equivalent AWS credentials. Preferred Experience Experience with MCP servers, multi-agent patterns, or LLM evaluation tooling (LangSmith, Langfuse, promptfoo). Experience with Terraform or CI/CD pipelines. Key Capabilities A strong candidate will bring: Breadth across the full stack, with depth in at least one AI platform Owns features end to end, from interface to infrastructure Cares about evaluation and reliability, not just the happy path Communicates clearly in demos, documents, and code review Client-facing mindset: understands client needs and translates business requirements into technical solutions Learns new tools and models fast, and shares what works Why Join Artefact At Artefact, data and AI are not abstract strategy topics. They are tools for creating business value, improving organizations, and helping people make better decisions. You will join a global community of data and AI experts who combine consulting, engineering, data science, marketing, and technology expertise. You will work on complex, high-impact problems with leading organizations and help shape how enterprises adopt AI responsibly and effectively. We value action, collaboration, learning, client trust, and shared knowledge. We believe that technology only matters when it is used, adopted, and translated into impact. Our values aren't decorations on a wall — they're how we actually work: There is always a way — We're builders and problem-solvers. An idea only counts if it gets executed. Client trust is won in the field — We show up, sleeves rolled up, working side by side with our clients. If it's not used, it's useless — We build for adoption and impact, not for slide decks. If it's not shared, we're not done — Knowledge shared compounds. We invest in each other's growth. We learn every day — In a field that moves this fast, standing still means falling behind. We embrace the challenge. How We Support Our People In addition to our values-driven culture, we offer a range of benefits and programs designed to support our employees' growth and well-being, including: Learning and Development: Work alongside a multidisciplinary team of AI, data, and consulting experts who are committed to continuous learning, knowledge sharing, and professional growth. Hybrid Flexibility: Our hybrid work model gives you the flexibility to balance collaboration, client needs, and personal commitments. Comprehensive Benefits: We offer a competitive benefits package that includes medical, dental, and vision coverage, a 401(k) plan with company matching, and paid parental leave. Time to Recharge: We believe sustainable performance matters. That's why we offer unlimited paid time off, giving you the flexibility to take the time you need. Growth Opportunities: As a rapidly growing organization, you'll have the opportunity to expand your skills, take on new challenges, and help shape the future of the company.
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.