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Key Responsibilities Design and develop Agentic AI systems with multi-step reasoning, tool use, and workflow orchestration.Integrate AI agents into client applications and business workflows.Build, fine-tune, and evaluate ML/LLM models using established training platforms and pipelines.Collaborate with clients and engineering teams to gather requirements and translate business problems into AI solutions.Integrate agentic workflows using APIs, SDKs, and platform-specific tools across web, mobile, and enterprise applications.Develop RAG pipelines, vector databases, embeddings, and prompt/context engineering strategies.Define evaluation metrics and conduct model/agent performance experiments.Optimize AI solutions for scalability, latency, cost, security, observability, and reliability.Work with data engineering, product, and QA teams to deliver production-ready AI features.Document architecture, model behavior, integration patterns, and deployment processes.Stay updated on the Agentic AI and ML ecosystem and recommend relevant frameworks and platforms.Required Skills & Experience 35 years of software engineering experience, including hands-on AI/ML application development.Experience building Agentic AI systems using LangChain, LangGraph, AutoGen, CrewAI, or similar frameworks.Experience integrating AI/ML solutions into web, mobile, or enterprise applications using APIs and SDKs.Knowledge of ML platforms such as AWS SageMaker, Google Vertex AI, Azure ML, or equivalent.Strong Python programming skills.Familiarity with JavaScript/TypeScript or mobile/native development is a plus.Strong understanding of LLMs, prompt engineering, embeddings, RAG, and vector databases.Experience with Pinecone, FAISS, Weaviate, or similar vector database technologies.Experience with AWS, Azure, or GCP cloud platforms.Hands-on experience with Docker and Kubernetes.Familiarity with MLOps, model versioning, ML CI/CD, monitoring, and observability.Strong client-facing communication and presentation skills.Ability to explain technical concepts to non-technical stakeholders.Experience in IT services/consulting environments is highly preferred.Ability to manage multiple client engagements and projects simultaneously. .
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.