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Position Overview: The client is seeking a highly motivated AI Developer with hands-on experience in Generative AI, Machine Learning, and Agentic AI technologies to develop intelligent solutions that automate business processes, enhance user productivity, and improve data-driven decision making. The successful candidate will design, build, and deploy AI-powered applications including AI agents, copilots, retrieval-augmented generation (RAG) solutions, conversational assistants, and workflow automation platforms. This role requires a strong software engineering foundation combined with practical experience implementing production-ready AI systems within enterprise environments. Key Responsibilities: AI & Agentic Solution Development Design, develop, and deploy AI-powered applications, AI agents, copilots, and intelligent automation solutions. Implement Agentic AI frameworks that leverage planning, reasoning, memory, orchestration, and tool usage capabilities. Develop Retrieval-Augmented Generation (RAG) solutions utilizing vector databases, enterprise knowledge repositories, and semantic search technologies. Build scalable AI services using Large Language Models (LLMs) and cloud-native architectures. Integrate AI capabilities into enterprise applications, data platforms, and business workflows. Develop APIs, microservices, and backend services that support AI applications. Build integrations with enterprise systems including CRM, MDM, data governance, and cloud platforms. Collaborate with product managers, architects, data engineers, and business stakeholders to translate business requirements into scalable AI solutions. Support the deployment, monitoring, and optimization of AI applications in development, test, and production environments. Implement LLMOps and MLOps best practices for model lifecycle management, version control, evaluation, monitoring, and governance. Monitor solution performance, usage, and operational metrics to continuously improve user experience and business outcomes. Ensure AI solutions comply with healthcare and life sciences regulatory requirements. Implement auditability, traceability, access controls, and monitoring across AI applications. Required Qualifications Education: Bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, or related field. Experience: 3–4 years of hands-on experience developing AI/ML solutions in enterprise environments. 2+ years of experience building solutions using Agentic AI technologies and Generative AI frameworks. Relevant experience delivering production-ready AI applications from concept through deployment. Preferred Technical Skills AI & Generative AI: Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agents and Multi-Agent Systems, Semantic Search and Embeddings & AI Evaluation Frameworks . Experience with one or more: LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, LlamaIndex Programming & Development: Python (required), SQL, REST APIs, Git/GitHub, FastAPI or equivalent backend frameworks Cloud & Data Platforms: experience with one or more Microsoft Azure, Azure OpenAI, Azure AI Foundry, AWS Bedrock & Google Cloud AI Services Data & Integration: Any of the below or more Vector Databases, Azure AI Search, PostgreSQL, Snowflake Preferred Qualifications: Experience developing AI solutions within healthcare, pharmaceutical, life sciences, or regulated industries. Familiarity with Master Data Management (MDM), Data Governance, and Stewardship solutions. Experience implementing LLMOps/MLOps pipelines. Knowledge of AI security, model evaluation, and responsible AI practices. Experience integrating AI services into Salesforce, enterprise workflow platforms, or customer-facing applications.
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.