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Senior AI R D Engineer Agent Orchestration Role Summary We are seeking a highly skilled Senior AI R D Engineer to focus on the cutting-edge field of agent orchestration This role is responsible for designing implementing and deploying sophisticated systems that enable AI agents to execute complex multi-step tasks autonomously A deep practical understanding of Large Language Models LLMs and the ability to rigorously evaluate agent system performance are non-negotiable What You Will Do Agent Orchestration Development Design and build advanced orchestration layers including planning memory management tool-use logic and iterative reasoning loops for autonomous agents Production Deployment Lead the deployment of LLM-powered features and agent systems into production environments ensuring scalability latency targets and reliability Mandatory Evaluation Mastery Own the definition implementation and analysis of agent and LLM evaluation benchmarks reference tests heuristics model-graded evaluation This includes metrics for helpfulness accuracy hallucination and safety Framework Implementation Leverage and contribute to modern agentic frameworks e g LangChain AutoGen CrewAI custom internal frameworks to build out capabilities Research to Production Translate the latest advancements in LLM and agent research into robust production-ready features collaborating closely with research scientists A B Testing Design and execute rigorous A B tests on prompts system settings and model versions making data-driven recommendations for rollouts or rollbacks Key Requirements 10 years of skilled experience in machine learning engineering NLP or AI R D Mastery of LLM Agent Evaluation Demonstrated expertise in setting up running and analyzing evaluation systems for LLMs and agentic workflows Production Experience Mandatory Extensive hands-on experience putting LLMs and at least one major agentic framework or equivalent custom architecture into high-volume production Strong software engineering foundation primarily in Python with experience writing clean maintainable and efficient code Experience in the advanced mechanisms and libraries around python pytorch langchain llama index deepeval scikit learn Deep understanding of LLM mechanisms prompt engineering fine-tuning RAG function tool calling Experience with observability tools logging tracing monitoring for real-time model performance diagnostics Bonus Points Background in academic research publications related to AI NLP or reinforcement learning Experience optimizing inference pipelines for performance and cost Familiarity with safety and guardrail systems for generative AI .
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.