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This requisition is not an active hiring opportunity. We are gathering resumes to support future project requirements and to build our talent pipeline. ERM is seeking an AI Data Engineer Consultant in North America to join our global Digital Services business. At ERM, we offer a robust combination of deep EHS&S experience together with broad environmental management information solution expertise. Our services span the entire information management life cycle, from assisting clients with information solutions portfolio assessment, strategy, technology evaluation and planning, to designing, testing and implementing enterprise-wide systems and innovative technologies. ERM has enduring values, which are fundamental to our business conduct. We are passionate about our people, their safety, well-being and development. ERMers take accountability, are client focused, and collaborate with colleagues across geographies. If you share our values, believe in sustainability and are motivated by opportunities to shape, build, and contribute to a team that makes a real impact to our clients businesses, ERM is the right place for you. We offer a flexible working environment and competitive salary. As a Consultant on our team, you will be a valuable asset amongst a diverse team of professionals striving to address business growth, daily business operations and environmental issues. You will work within an environment that promotes proactive cooperation and motivates individuals to maintain a positive attitude in order to consistently deliver quality services and technical solutions. Lead the next wave of AIdriven digital transformation If you thrive at the frontier of artificial intelligence, data engineering, and modern software developmentand want your work to move beyond experimentation into realworld impactthis role offers a unique opportunity to shape how AI delivers value at scale. As an AI Data Engineer, you will help define how intelligent systems turn complex data into actionable insight for clients navigating their most critical challenges. Why This Role Matters Artificial intelligence is rapidly reshaping how organizations make decisions, manage risk, and unlock value from data. This role plays a pivotal part in transforming AI from a promising concept into a dependable, productionready capability. You will architect intelligent pipelines, orchestrate advanced AI workflows, and deliver trusted outputs that directly influence business decisions, strategy, and outcomes. What Your Impact Is Enable AIdriven solutions that transform messy, fragmented data into structured, businessready outputs. Design and scale intelligent workflows that combine LLMs, automation, and modern data engineering practices. Shape customerfacing solutions by bridging AI research, robust engineering, and usercentric design. Help evolve how organizations operationalize AI responsibly, effectively, and at enterprise scale. What Youll Bring Required University degree holder in an environmental or technical field such as Environmental Sciences, Information Technology, Computer Science, Engineering, Management Information Systems, or Theoretical Business. 4-6 years of relevant experience in an AI data engineering and or EHS-related field. Diversified information technology background and knowledge of EHS software, methodologies, domains and technology an advantage but not required. (Environmental Compliance, Industrial Hygiene and Safety, Occupational Health, Occupational Hygiene, Audit Management, Incident Management & Risk Assessment) Handson experience working with large language models (OpenAI, Anthropic, Mistral, or opensource equivalents). Deep understanding of embeddings, vector search, semantic similarity, and RAG architectures. Strong proficiency in Python with experience using async patterns, data libraries (pandas, polars), and AI SDKs. Experience implementing AI workflows using LangChain, LlamaIndex, or similar orchestration frameworks. Solid skills in SQL, relational data modeling, and performance optimization. Proven ability to generate and manipulate Excel, PDF, and Word documents programmatically. Experience building APIs using FastAPI, .NET, or Node.js and integrating them into production systems. Preferred Frontend development experience using Vue 3 (Composition API) and TypeScript. Experience with vector databases and AIoriented data storage patterns. Familiarity with containerization, cloud platforms, or serverless architectures. Background in NLP, document intelligence, or data enrichment pipelines. Exposure to monorepo or largescale project tooling (e.g., Turborepo, Nx). Key Responsibilities Design and implement AIpowered data pipelines to extract, clean, enrich, and transform structured and unstructured data. Orchestrate LLMs to .
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.