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We're looking for an engineer with hands-on experience building and evaluating GenAI services - from RAG and agentic reasoning systems to production-grade LLM deployments. You'll work closely with Frontend and Backend teams to bring AI agents into real products, with a strong focus on reliability, safety, and shipping working prototypes fast. Hard Skills: Practical experience developing and evaluating GenAI services, including RAG systems, understanding of the "ReAct" (Reasoning + Acting) paradigm and Agentic RAG, LLM API integration, and prompt/context engineering, as well as training, fine-tuning, and deploying ML models in production environments. Knowledge of ML/GenAI frameworks: LangGraph or LangChain, PyTorch / TensorFlow, Hugging Face, OpenAI/Anthropic SDK. Practical commercial experience working with AI models via API (Gemini, Anthropic) and self-hosted models (Llama 3, Mistral, Mixtral), with an understanding of model differences based on functional/non-functional requirements (FR/NFR). Deep understanding of how LLMs interact with external APIs via Function Calling. Experience with vector databases, semantic search methods, and principles of database structuring and cleaning. Practical experience with at least one cloud platform (AWS, GCP, or Azure). Proficiency in Python and understanding of asynchronous programming. Understanding of the AI model lifecycle: monitoring, versioning, and quality evaluation (RAGAS, DeepEval), with hands-on experience using these tools. Experience with Guardrails: setting hard constraints on conversation topics and agent actions, filters that automatically strip personal data before sending requests to external LLMs, and the ability to build output filters that fact-check generated responses before they're displayed. Deterministic Logic Integration — running AI agents on strict schemas to prevent the model from "making things up." A plus: knowledge of automated testing approaches for evaluating responses across large datasets to measure hallucination rates before MVP launch. Knowledge of Human-in-the-loop mechanisms, ensuring agents cannot execute actions without final user verification. Ability to design memory systems that store context from a client's previous conversations and operations for personalization (Long-term Memory & User Context). Soft Skills: Ability to clearly communicate complex technical concepts and mentor team members. Ability to quickly test and evaluate new libraries and approaches. Analytical problem solving - debugging complex "black boxes" and understanding why an agent behaves unpredictably. Focus on delivering a working prototype rather than a perfect research paper. Close collaboration with Frontend and Backend developers to seamlessly integrate AI agents into the required environment. We offer*: Flexible working format - remote, office-based or flexible A competitive salary and good compensation package Personalized career growth Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more) Active tech communities with regular knowledge sharing Education reimbursement Memorable anniversary presents Corporate events and team buildings Other location-specific benefits *not applicable for freelancers
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.