AI Engineer

EXL

AI Engineer responsible for developing agentic AI systems across complex workflows using LLMs and frameworks. Implementing memory, tool-use, and security strategies within production environments.

Posted 6/10/2026full-timeBengaluru • 🇮🇳 IndiaJuniorMid-LevelWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonReactSQL

About the role

Key responsibilities & impact

Design and implement agentic AI systems (single and multi-agent) with tool use, memory, and fallback mechanisms.
Build production-grade agents using frameworks like LangGraph, AutoGen, CrewAI, or custom LLM orchestration layers.
Implement agent reasoning loops including planning, tool selection, execution, observation, and re-planning with safety guardrails.
Develop prompt and context engineering strategies for reliable, grounded LLM outputs.
Design agent orchestration workflows include task routing, parallel execution, state management, retries, and human-in-the-loop escalation.
Build evaluation frameworks for LLMs and agents including automated testing, adversarial testing, and performance benchmarking.
Implement retrieval and grounding using vector databases, embeddings, and knowledge graphs for contextual accuracy.
Ensure observability of agent systems by tracing LLM calls, tool usage, and decision paths using monitoring tools.
Apply security and governance controls including prompt injection defense, access control, and safe tool execution.
Optimize agent systems for latency, cost, and scalability in production environments.
Build CI/CD pipelines for agent workflows including versioning, testing, and controlled deployments.
Integrate agents with enterprise systems and APIs to automate end-to-end business workflows.
Design feedback loops using production traces and evaluation signals to continuously improve agent performance.
Hands-on experience in fine-tuning LLMs for domain-specific applications using LoRA, PEFT, QLoRA, RLHF, instruction tuning, and other parameter-efficient adaptation techniques.
Stay current with emerging agentic AI frameworks, research, and best practices for production deployment

Requirements

What you’ll need

Minimum 2 years of AI engineering experience, with at least 1 year focused on LLM/agent systems in production.
Hands-on experience designing agentic architectures: ReAct, plan-and-execute, reflection loops, tool-use patterns.
Proficiency in Python; experience with at least one agent framework (LangChain/LangGraph, AutoGen, CrewAI, Semantic Kernel, or equivalent).
Strong understanding of prompt engineering, context window management, and structured output extraction.
Experience building and testing tool-use integrations: REST APIs, code interpreters, vector databases, SQL executors.
Familiarity with evaluation frameworks for LLM outputs (RAGAS, custom eval harnesses, LLM-as-judge patterns).
Understanding of agent safety concerns: prompt injection, tool misuse, hallucination detection, and mitigation strategies.
Experience with cloud infrastructure (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
Experience with MLOps, AIOps tooling (MLflow, Weights & Biases, experiment tracking).
Strong experience designing and building memory and caching layers for agentic AI systems, including conversational memory, semantic retrieval, context optimization, and token cost reduction strategies for scalable production deployments

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account EXL Website LinkedIn All Job Openings 10,000+ employees 💰 $2M Venture Round on 2015-01 Choosing a digital partner is about more than capabilities — it’s about collaboration and character. AI Engineer 🔥 14 minutes ago 🏢 Bengaluru – Onsite ⏰ Full Time 🟢 Junior 🟡 Mid-level 🤖 AI Engineer AWS Azure Cloud Docker Google Cloud Platform Kubernetes Python React SQL Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Design and implement agentic AI systems (single and multi-agent) with tool use, memory, and fallback mechanisms.
Build production-grade agents using frameworks like LangGraph, AutoGen, CrewAI, or custom LLM orchestration layers.
Implement agent reasoning loops including planning, tool selection, execution, observation, and re-planning with safety guardrails.
Develop prompt and context engineering strategies for reliable, grounded LLM outputs.
Design agent orchestration workflows include task routing, parallel execution, state management, retries, and human-in-the-loop escalation.
Build evaluation frameworks for LLMs and agents including automated testing, adversarial testing, and performance benchmarking.
Implement retrieval and grounding using vector databases, embeddings, and knowledge graphs for contextual accuracy.
Ensure observability of agent systems by tracing LLM calls, tool usage, and decision paths using monitoring tools.
Apply security and governance controls including prompt injection defense, access control, and safe tool execution.
Optimize agent systems for latency, cost, and scalability in production environments.
Build CI/CD pipelines for agent workflows including versioning, testing, and controlled deployments.
Integrate agents with enterprise systems and APIs to automate end-to-end business workflows.
Design feedback loops using production traces and evaluation signals to continuously improve agent performance.
Hands-on experience in fine-tuning LLMs for domain-specific applications using LoRA, PEFT, QLoRA, RLHF, instruction tuning, and other parameter-efficient adaptation techniques.
Stay current with emerging agentic AI frameworks, research, and best practices for production deployment 🎯 Requirements
Minimum 2 years of AI engineering experience, with at least 1 year focused on LLM/agent systems in production.
Hands-on experience designing agentic architectures: ReAct, plan-and-execute, reflection loops, tool-use patterns.
Proficiency in Python; experience with at least one agent framework (LangChain/LangGraph, AutoGen, CrewAI, Semantic Kernel, or equivalent).
Strong understanding of prompt engineering, context window management, and structured output extraction.
Experience building and testing tool-use integrations: REST APIs, code interpreters, vector databases, SQL executors.
Familiarity with evaluation frameworks for LLM outputs (RAGAS, custom eval harnesses, LLM-as-judge patterns).
Understanding of agent safety concerns: prompt injection, tool misuse, hallucination detection, and mitigation strategies.
Experience with cloud infrastructure (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
Experience with MLOps, AIOps tooling (MLflow, Weights & Biases, experiment tracking).
Strong experience designing and building memory and caching layers for agentic AI systems, including conversational memory, semantic retrieval, context optimization, and token cost reduction strategies for scalable production deployments Apply Now 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score Similar Jobs AI Developer, Technology Engineer 🕒 November 13, 2025 NVIDIA 10,000+ employees 🤖 Artificial Intelligence 🎮 Gaming Website LinkedIn All Job Openings AI Developer Technology Engineer at NVIDIA developing AI solutions and optimizing GPU performance with deep learning techniques. Collaborating with architecture and research teams for cutting-edge advancements. 🏢 Bengaluru – Onsite ⏰ Full Time 🟢 Junior 🟡 Mid-level 🤖 AI Engineer AI Developer 🕒 September 10, 2025 Sara Foundation Africa 1 - 10 📚 Education 🌍 Social Impact Website LinkedIn All Job Openings AI Developer in Bengaluru building AI solutions. Full-time role; submit resume and portfolio links. 🏢 Bengaluru – Onsite ⏰ Full Time 🟡 Mid-level 🟠 Senior 🤖 AI Engineer View More AI Engineer Jobs 🌐 Worldwide Built by Lior Neu-ner. I'd love to hear your feedback — Get in touch via DM or support@remoterocketship.com Search Search Jobs by country Search jobs by city Search jobs by job title Search entry-level jobs Search junior-level jobs Search senior-level jobs Search jobs by tech stack Search jobs by contract type Search remote internships Search remote part-time jobs Remote jobs Anywhere in the World Companies Hiring Anywhere in the World Companies Hiring Sales People Anywhere in the World Companies Hiring Software Engineers Anywhere in the World Resources Advice Tips for finding remote jobs Interview questions and answers Resume examples Cover letter examples Post a job Affiliates Privacy policy Terms of service Job board SEO course AI Apply Copilot OpenClaw job finder Jobs by Country Remote jobs anywhere in the world (Worldwide remote jobs) Remote jobs United States Remote jobs Australia Remote jobs Brazil Remote jobs Canada Remote jobs France Remote jobs Ireland Remote jobs Germany Remote jobs Netherlands Remote jobs Spain Remote jobs UK Popular Jobs Remote data analyst jobs Remote customer support jobs Remote executive assistant jobs Remote marketing jobs Remote product designer jobs Remote product manager jobs Remote project manager jobs Remote recruiter jobs Remote sales jobs Remote software engineer jobs Jobs by Type Remote full-time jobs Remote part-time jobs Remote contract jobs Remote internship jobs Remote entry-level jobs Remote jobs with no experience required Remote junior jobs (1-3 years of experience) Digital nomad jobs Remote jobs with no degree required Freelance remote jobs Temporary remote jobs Remote jobs hiring now Stay at home mom jobs

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI engineeringLLM systemsagentic architecturesPythonprompt engineeringtool-use integrationsevaluation frameworkscloud infrastructureMLOpsmemory and caching layers