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All roles AI / AppliedBangalore, IN BHIVE Workspace, AKR Tech Park (Kudlu Gate)Full-time Hybrid5+ years (3+ years shipping LLMs in production) AI Engineer MidSenior Build and ship the applied AI layer the in-product copilot, semantic search, rule-suggestion engine and structured-output features that customers use every day. LLM FeaturesRAGPrompt EngineeringEval HarnessesPython Team AI / Applied Location Bangalore, IN BHIVE Workspace, AKR Tech Park (Kudlu Gate) Experience 5+ years (3+ years shipping LLMs in production) Tech stack LangChain LlamaIndexOpenAI Anthropic Gemini AWS BedrockPinecone pgvector QdrantPython (async) FastAPIBLEU ROUGE BERTScoreLoRA QLoRA PEFT Apply for this role What youll do 01 Implement, evaluate and ship LLM features end-to-end RAG, tool-use, agents and fine-tunes02 Design and iterate on prompt strategies: chain-of-thought, few-shot, structured outputs, function calling03 Build the in-product AI copilot answering steward questions, suggesting rules and explaining match decisions04 Develop evaluation harnesses with telemetry, guardrails and offline + online evals05 Integrate and benchmark third-party APIs (OpenAI, Anthropic, Gemini, AWS Bedrock) for cost and latency06 Collaborate with the ML Engineer on embedding strategies, retrieval quality and rerankers07 Work with backend engineers to package AI components as well-defined, observable microservices08 Maintain prompt and model version control with rollback capability for production AI features09 Document system behaviour, failure modes and known limitations for every shipped AI feature What were looking for 5+ years software engineering experience; 3+ years working directly with LLMs in production Strong Python async APIs, data pipelines and clean, testable code Hands-on with LangChain, LlamaIndex or equivalent orchestration frameworks Experience with OpenAI / Anthropic / Gemini APIs including function calling and structured outputs Working knowledge of embedding models and vector databases (Pinecone, pgvector, Qdrant) Strong NLP fundamentals: tokenization, NER, relation extraction and summarisation Solid grasp of evaluation methodology BLEU/ROUGE/BERTScore plus task-specific evals Experience shipping AI features end-to-end from prototype to production Nice to have + Experience with B2B data platforms, MDM, entity resolution or recommendation systems+ Exposure to fine-tuning LLMs (LoRA / QLoRA, PEFT, instruction tuning)+ Familiarity with Salesforce or Databricks ecosystems .
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.