10 Autonomous Agents Jobs

If you are a smart, self-motivated Machine Learning Scientist with a passion for advancing the field of Generative AI, an excellent opportunity awaits you. EXL, a rapidly expanding global digital data-led AI transformation solutions company, is seeking candidates with deep expertise in developing and fine-tuning Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic solutions, and knowledge graph technologies to drive innovative solutions in Generative AI. You will have the chance to be at the forefront of pioneering advancements in AI, working alongside bright minds in an exciting R&D environment to build cutting-edge capabilities that redefine the future of artificial intelligence. In this role, you will develop initiatives in the Generative AI domain, focusing on cutting-edge technologies like LLMs, RAG, and autonomous agents. You will design and implement advanced workflows for integrating LLMs into real-world applications across domains such as Finance, Insurance, and Healthcare. Additionally, you will drive the development of retrieval-augmented systems by combining LLMs with document retrieval, clustering, and search techniques. Keeping abreast of AI advancements is essential, as you will be required to read, adapt, and implement cutting-edge research to solve real-world challenges. Documenting research findings, methodologies, and implementations for internal and external stakeholders will also be part of your responsibilities. Qualifications: - Experience: 2-5 years in AI/ML research and development, with at least 1-2 years focusing on Generative AI, LLMs, or related fields. - Education: Masters or PhD in Computer Science, AI, or a related field from a top-tier institution is highly preferred. Required Skills: - Core Expertise: Proven experience with Large Language Models (e.g., GPT-4, BERT, LLaMA, PaLM) and fine-tuning them for domain-specific applications. In-depth knowledge of Retrieval-Augmented Generation workflows and hands-on experience with autonomous agents. - Tools & Frameworks: Proficiency in deep learning frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Experience with distributed training and optimization on GPUs and TPUs. Familiarity with cloud ecosystems (AWS, Azure, Google Cloud) practices for scalable deployment. - Research & Development: Ability to read and adapt cutting-edge research papers for applied solutions in LLMs and knowledge graphs. Expertise in domain adaptation, few-shot learning, and zero-shot reasoning. Strong understanding of generative models and their integration with LLMs. - Problem Solving: Demonstrated ability to address challenges in unstructured data processing, including NLP and multimodal scenarios. Experience with document retrieval, clustering, and unsupervised learning techniques. Preferred Skills: - Experience with LLM fine-tuning and building Agentic systems for domain LLMs. Experience with reinforcement learning and fine-tuning via RLHF. Knowledge of large-scale optimization methods and efficient model compression techniques. Strong collaboration and communication skills, with a proven ability to lead teams. Experience with MoE based architecture and knowledge of federated learning.,

As an IPA Developer at our company in Hyderabad (Hybrid), you will be responsible for architecting automation solutions across various platforms such as UiPath, Power Automate, AA, Blue Prism, Pega, and Appian. Your role will involve assessing automation maturity, identifying gaps and opportunities, and recommending tools and platforms for RPA, AI, and orchestration. You will lead the design and implementation of intelligent automation using RPA, BPM, ML, NLP, and other technologies. Creating automation roadmaps for healthcare workflows, defining business cases, and prioritizing automation initiatives will also be part of your responsibilities. Moreover, you will apply architecture and governance principles to ensure scalable and secure AI solutions. Your leadership will be crucial in agentic automation, collaborating with product owners, engineers, and SMEs in agile environments. To excel in this role, you should have at least 15 years of experience in automation architecture and consulting, with hands-on expertise in RPA (UiPath, AA, Blue Prism), BPM, and AI tools. Proficiency in fit-gap analysis, platform selection, and ROI modeling is essential, along with a strong understanding of TOGAF/Zachman and integration patterns. Experience in AI integration, particularly in ML, NLP, LLMs, and document understanding, will be beneficial. Preferred qualifications include healthcare workflow experience, certification as an Architect in UiPath, AA, or Power Platform, and excellent communication and stakeholder management skills. Knowledge of HIPAA/HITECH, AI governance, LLM prompt engineering, healthcare transformation/consulting, and exposure to Process Intelligence, AI Ops, and Autonomous Agents are considered nice-to-have skills. This is a full-time position that requires in-person work at our Hyderabad office. If you are passionate about automation, AI, and healthcare workflows, and possess the necessary qualifications and skills, we encourage you to apply for this role.,

Role & responsibilities Microsoft AI tools and services, Agentic AI paradigms ,including autonomous agents, multi-agent systems, and AI orchestration frameworks. Experience with cloud platforms (Azure preferred). Knowledge of MLOps practices and tools.

At InnovationM , we're shaping the future of enterprise AI and are looking for a Senior Agentic AI Engineer to lead the design and development of cutting-edge agentic frameworks. Youll help build a scalable AI foundation that empowers multiple teams to deploy intelligent agents with autonomy, memory, and reasoning capabilities. Key Skills: Python | LangGraph | CrewAI | RAG | LLMs | Agentic Frameworks Tool Integration | Vector Databases | Autonomous Decision-Making Human-in-the-Loop | Secure, Scalable Architectures What Youll Do: Architect enterprise-grade AI frameworks Build reusable agentic patterns using LangGraph, CrewAI, AutoGPT Enable tools like APIs, vector stores, RPA, and internal services Collaborate across teams to bring autonomy into complex workflows Mentor and guide teams on the future of agentic AI Why Join Us? Work on the latest in AI/ML and agentic systems Engage with large-scale clients and impactful projects Thrive in a culture of innovation, learning & development Location: Noida Sec-126 l 5 Days work from Office Apply now: nikita.gautam@innovationm.com

The company you will be joining, TechGlobal, is a renowned global leader in strategy, technology consulting, and digital services, operating in over 100 countries. TechGlobal is dedicated to assisting businesses in embracing cutting-edge solutions for their digital transformation, aiming to make them digital-first and digital-ready. With a workforce of over 600,000 employees globally, including 200,000 in India, the company has a strong presence in the country with development centers in more than 10 locations across Tier 1 and Tier 2 cities. TechGlobal is known for its people-centric and employee-friendly policies, offering hybrid work options and flexible location choices due to its extensive Pan India presence. Your role at TechGlobal will involve developing applications and systems that leverage AI tools and Cloud AI services, ensuring the creation of cloud or on-prem application pipelines with production-ready quality. You will be expected to integrate GenAI models into the solutions, exploring areas such as deep learning, neural networks, chatbots, and image processing. Key Responsibilities: - Lead research and development in agentic architectures, autonomous agents, human-agent collaboration, and model/agent drift detection. - Design and prototype autonomous agents for practical applications like enterprise automation, digital assistants, and healthcare autonomous agents. - Collaborate with solutioning, delivery, and engineering teams to incorporate agentic capabilities into scalable systems for various industries. - Work with the Responsible AI team to embed policies in the solutions, collaborate with consulting teams to provide technical expertise in AI, and engage with academia and industry partners for advancing research boundaries. - Share innovative research findings in top AI forums and conferences. - Develop a strong AI talent pool and promote a culture of continuous learning within the organization, while mentoring a team of researchers and engineers. - Provide consulting and solutioning support for complex client issues by leveraging niche AI skills and utilizing advanced frameworks and accelerators. Skills Required: - A Ph.D. in Computer Science, Electrical Engineering, Electronics, Electronics and Communication, Data Science/AI, Mathematics, or Statistics from prestigious institutions like IITs, IISc, IIIT, or ISI. - A total of 12-20 years of experience with at least 5 years of relevant experience post-PhD. - Profound expertise in reinforcement learning, autonomous agents, and multi-agent systems. - In-depth understanding of LLMs and their application in agentic workflows. - Hands-on experience with frameworks such as LangChain, AutoGPT, or similar tools. - Demonstrated history of innovation and publications. Qualifications & Experience: - A Ph.D. in Computer Science, Electrical Engineering, Electronics, Electronics and Communication, Data Science/AI, Mathematics, or Statistics from esteemed institutions like IITs, IISc, IIIT, or ISI. - 12 to 20 years of overall experience in relevant fields.,

As a Senior AI Engineer specialized in Voice AI and Autonomous Agents at Spyne, you will be responsible for owning and building Spynes in-house voice bot stack. This pivotal role involves leveraging your expertise in LLMs, ASR/TTS, and voice UX to develop immersive, human-like conversations between auto dealerships and their customers. Located in Gurugram, you will work from the office five days a week to drive the development of cutting-edge AI solutions in the automotive retail sector. Your primary responsibilities will include: - Voice AI Stack Ownership: Developing and managing the complete voice bot pipeline encompassing ASR, NLU, dialog state management, tool calling, and TTS to deliver a seamless conversation experience. - LLM Orchestration & Tooling: Designing systems utilizing MCP to facilitate structured context exchange between real-time ASR, memory, APIs, and the LLM. - RAG Integration: Implementing retrieval-augmented generation to support responses based on dealership knowledge bases, inventory data, recall lookups, and FAQs. - Vector Store & Memory: Creating scalable vector-based search functionalities for dynamic FAQ handling, call recall, and user-specific memory embedding. - Latency Optimization: Engineering low-latency, streaming ASR + TTS pipelines and optimizing turn-taking models for natural conversations. - Model Tuning & Hallucination Control: Customizing tone, reducing hallucinations, and aligning responses with business objectives via fine-tuning, LoRA, or instruction tuning. - Instrumentation & QA Looping: Establishing robust observability, conducting real-time call QA processes, and analyzing interruptions, hallucinations, and fallbacks. - Cross-functional Collaboration: Collaborating closely with product, infra, and leadership teams to scale the voice bot solution to numerous US dealerships effectively. To excel in this role, you should possess: - Architectural Thinking: Ability to comprehend the integration of ASR, LLMs, memory, and tools and design modular, observable, and resilient systems. - LLM Tooling Mastery: Proficiency in implementing tool calling, retrieval pipelines, function calls, or prompt chaining across various workflows. - Fluency in Vector Search & RAG: Expertise in chunking, embedding, indexing, and retrieval processes while avoiding prompt bloat and token overflow. - Latency-First Mindset: Capability to identify and rectify token delays, optimize API round-trip time, and ensure human-like call interactions. - Grounding > Hallucination: Skill in tracing hallucinations to weak prompts, lack of guardrails, or tool access deficiencies and addressing them effectively. - Prototyping Skills: Comfort with building from scratch and rapid iteration using open-source or hosted tools as required. Requirements for this role include: - 5+ years of experience in AI/ML or voice/NLP systems with real-time exposure. - Profound knowledge of LLM orchestration, RAG, vector search, and prompt engineering. - Experience with MCP-style architectures and structured context pipelines between LLMs and APIs/tools. - Familiarity with integrating ASR (Whisper/Deepgram), TTS (ElevenLabs/Coqui), and OpenAI/GPT-style models. - Strong understanding of latency optimization, streaming inference, and real-time audio pipelines. - Proficiency in Python, FastAPI, vector DBs (Pinecone, Weaviate, FAISS), and cloud infrastructures (AWS/GCP). - Solid debugging, logging, and QA capabilities for hallucination, grounding, and UX analysis. Join Spyne for a real-world AI impact, a superior team balancing speed with technical depth, high autonomy, and visibility from day one, accelerated career growth, MacBook along with essential tools, and a flat structure focused on meaningful work without unnecessary bureaucracy.,

As a Senior AI Engineer - Voice AI / Autonomous Agents at Spyne, you will have the opportunity to own and build Spynes in-house voice bot stack. In this high-impact individual contributor role, you will be at the intersection of LLMs, ASR/TTS, and voice UX, focusing on creating deeply human, latency-optimized conversations between auto dealerships and their customers. Your main responsibilities will include: Voice AI Stack Ownership: Building and owning the end-to-end voice bot pipeline, including ASR, NLU, dialog state management, tool calling, and TTS to deliver a natural, human-like conversation experience. LLM Orchestration & Tooling: Architecting systems using MCP (Model Context Protocol) to mediate structured context between real-time ASR, memory, APIs, and the LLM. RAG Integration: Implementing retrieval-augmented generation to ground responses using dealership knowledge bases, inventory data, recall lookups, and FAQs. Vector Store & Memory: Designing scalable vector-based search for dynamic FAQ handling, call recall, and user-specific memory embedding. Latency Optimization: Engineering low-latency, streaming ASR + TTS pipelines and fine-tuning turn-taking models for natural conversation. Model Tuning & Hallucination Control: Using fine-tuning, LoRA, or instruction tuning to customize tone, reduce hallucinations, and align responses to business goals. Instrumentation & QA Looping: Building robust observability, running real-time call QA pipelines, and analyzing interruptions, hallucinations, and fallbacks. Cross-functional Collaboration: Working closely with product, infra, and leadership to scale this bot to thousands of US dealerships. To be successful in this role, you should possess: Architect-level thinking: Understanding how ASR, LLMs, memory, and tools fit together and having the ability to design modular, observable, and resilient systems. LLM Tooling Mastery: Implementing tool calling, retrieval pipelines, function calls, or prompt chaining across multiple workflows. Fluency in Vector Search & RAG: Knowing how to chunk, embed, index, and retrieve, while avoiding prompt bloat and token overflow. Latency-First Mindset: Debugging token delays, understanding the cost of each API hop, and optimizing round-trip time to maintain human-like interactions. Grounding > Hallucination: Tracing hallucinations back to weak prompts, missing guardrails, or lack of tool access and effectively addressing them. Prototyper at heart: Being unafraid of building from scratch and iterating quickly, utilizing open-source or hosted tools as necessary. The ideal candidate will have: 5+ years of experience in AI/ML or voice/NLP systems with real-time experience. Deep knowledge of LLM orchestration, RAG, vector search, and prompt engineering. Experience with MCP-style architectures or structured context pipelines between LLMs and APIs/tools. Experience integrating ASR (Whisper/Deepgram), TTS (ElevenLabs/Coqui), and OpenAI/GPT-style models. Solid understanding of latency optimization, streaming inference, and real-time audio pipelines. Hands-on experience with Python, FastAPI, vector DBs (Pinecone, Weaviate, FAISS), and cloud infra (AWS/GCP). Strong debugging, logging, and QA instincts for hallucination, grounding, and UX behavior. Working at Spyne offers real-world AI impact at scale, a high-performing team that balances speed with technical depth, high autonomy and visibility from day one, rapid career acceleration, access to MacBook and all necessary tools and compute, a flat structure with real work focus, and no BS. Join us in redefining how cars are marketed and sold with cutting-edge Generative AI.,

At InnovationM , we're shaping the future of enterprise AI and are looking for a Senior Agentic AI Engineer to lead the design and development of cutting-edge agentic frameworks. Youll help build a scalable AI foundation that empowers multiple teams to deploy intelligent agents with autonomy, memory, and reasoning capabilities. Key Skills: Python | LangGraph | CrewAI | RAG | LLMs | Agentic Frameworks Tool Integration | Vector Databases | Autonomous Decision-Making Human-in-the-Loop | Secure, Scalable Architectures What Youll Do: Architect enterprise-grade AI frameworks Build reusable agentic patterns using LangGraph, CrewAI, AutoGPT Enable tools like APIs, vector stores, RPA, and internal services Collaborate across teams to bring autonomy into complex workflows Mentor and guide teams on the future of agentic AI Why Join Us? Work on the latest in AI/ML and agentic systems Engage with large-scale clients and impactful projects Thrive in a culture of innovation, learning & development Location: Noida Sec-126 l 5 Days work from Office Apply now: neha.sharma@innovationm.com

Design and deploy autonomous AI agents using LLMs and frameworks like LangChain or AutoGPT. Collaborate on real-world applications, optimize agent workflows, and ensure safe, scalable AI solutions. Strong Python and GenAI experience required.

An Ideal Candidate: 5+ years in software development; 2+ years in AI tools/frameworks. Technical Skills: Python and .NET development. Multi-agent orchestration (e.g., semantic kernel, autogen). RAG techniques (e.g., GraphRAG). Expertise in Model Context Protocol (MCP). Experience around developing autonomous coding agents and research agents. Preferred Qualifications Experience with distributed systems and cloud-based AI architectures. Knowledge in NLP, knowledge graphs, and semantic reasoning. Experience with Azure DevOps and Azure Cloud Key Competencies: 1.Seeking an AI Developer with a software development background, expertise in AI tools, multi-agent orchestration frameworks, RAG techniques, and Model Context Protocol (MCP). Proficiency in Python, .NET, and hands-on experience with coding agents and research agents is preferable. 2. Responsibilities Build and optimize AI systems using semantic kernel, autogen, and multi-agent frameworks. Develop solutions leveraging retrieval-augmented generation (RAG), preferably GraphRAG. Integrate and optimize workflows using Model Context Protocol (MCP). Write scalable and maintainable code in Python and .NET. Design autonomous coding agents and research agents for problem-solving. 3.Research emerging AI tools and methods for practical application. 4.Debug, troubleshoot, and optimize AI systems for performance and reliability. Ref:JN-062025-794725