AI/ML at Deqode · Remote only · 4 - 8 years · ₹4L - ₹12L / yr · Bootstrapped · Remote only · Posted 17 Feb 2026

Job Description -
Profile: AI/ML
Experience: 4-8 Years
Mode: Remote
Mandatory Skills - AI/ML, LLM, RAG, Agentic AI, Traditional ML, GCP
Must-Have:
● Proven experience as an AI/ML specifically with a focus on Generative AI and Large Language Models (LLMs) in production.
● Deep expertise in building Agentic Workflows using frameworks like LangChain, LangGraph, or AutoGen.
● Strong proficiency in designing RAG (Retrieval-Augmented Generation)
● Experience with Function Calling/Tool Use in LLMs to connect AI models with external APIs (REST/gRPC) for transactional tasks
● Hands-on experience with Google Cloud Platform (GCP), specifically Vertex AI, Model Garden, and deploying models on GPUs
● Proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).

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🚀 WE’RE HIRING | AI/ML GENERATIVE AI ENGINEER
📍 Location: Remote
💼 Experience: 5+ Years
🔄 Position: Contract – Extendable
🔹 ROLE HIGHLIGHTS
➤ Build and deploy AI/ML amp; Generative AI solutions
➤ Develop LLM, RAG, NLP, Recommendation amp; Predictive solutions
➤ Work on AI Agents, Chatbots, Computer Vision amp; Content Intelligence
➤ Build ML models using PyTorch, TensorFlow, Keras amp; Scikit-learn
➤ Develop RAG solutions using LangChain, LlamaIndex, FAISS/Milvus
➤ Integrate OpenAI, Azure OpenAI, AWS Bedrock, Vertex AI amp; Hugging Face
➤ Build scalable AI APIs using Python, FastAPI/Flask/Django
➤ Contribute to Private AI amp; Smart Agentic Systems
⚙️ MUST-HAVE SKILLS
◆ Python – 3+ years
◆ AI/ML – 5+ years
◆ Generative AI – 2+ years
◆ LLMs, RAG, Embeddings , Transformers
◆ ML/DL, NLP amp; Predictive Analytics
◆ Cloud AI Platforms – Azure / AWS / GCP
◆ AI/ML Deployment | MLOps
Interview Process - F2F Round at Pune Location
Job Description – AI Engineer (End-to-End Development & Deployment)
Role Summary
We are looking for an AI Engineer with hands-on experience in designing, developing, deploying, and maintaining Generative/Agentic AI solutions in production. The ideal candidate should have end-to-end ownership of AI applications, from development to deployment, monitoring, and optimization.
Key Responsibilities
● Design, build, and deploy Generative/Agentic AI solutions.
● Develop applications using LLMs, RAG, AI agents, and vector databases.
● Build scalable APIs and integrate AI solutions with enterprise applications.
● Implement CI/CD pipelines, containerization, and MLOps best practices.
● Monitor, optimize, and maintain production AI systems.
● Collaborate with cross-functional teams to deliver business-driven AI solutions.
Required Skills
● Strong programming skills in Python.
● Experience with vector databases (e.g., Pinecone, FAISS, ChromaDB) and graph memory systems
● Knowledge of atleast one agent development framework: Google ADK (preferred), LangChain/LangGraph/LlamaIndex, CrewAI
● Experience with LLMs, RAG, GenAI, AgenticAI Agents
● Hands-on experience with FastAPI, and REST APIs.
● Knowledge of Docker, Kubernetes, Git, CI/CD.
● Experience with AWS, Azure, or GCP.
● Experience with security compliance, monitoring and observability tools such as AWS CloudWatch, Azure Monitor, Google Cloud Monitoring.
Role Overview
We are looking for an experienced AI/ML Engineer with strong expertise in Python, Generative AI, LLMs, LangChain, and LangGraph. The candidate will be responsible for designing and developing AI-powered applications, intelligent agents, and scalable LLM-based solutions.
Key Responsibilities
- Design and develop AI/ML and Generative AI applications using Python and modern LLM technologies.
- Build LLM-based applications and AI agents using LangChain and LangGraph.
- Develop agentic workflows involving tool calling, memory, reasoning, and multi-step orchestration.
- Integrate LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or other foundation models.
- Develop RAG (Retrieval-Augmented Generation) pipelines using vector databases.
- Work with embeddings, prompt engineering, semantic search, and document processing.
- Develop scalable APIs and backend services using Python, FastAPI, or Flask.
- Build and integrate AI solutions with existing applications and enterprise systems.
- Deploy and maintain AI/ML solutions on cloud platforms.
- Collaborate with data scientists, software engineers, and product teams to develop business-focused AI solutions.
Required Skills
- Strong hands-on experience in Python programming.
- Strong experience in AI/ML and Generative AI.
- Hands-on experience with LLMs and LLM-based application development.
- Strong experience with LangChain and/or LangGraph.
- Experience building AI Agents / Agentic AI workflows.
- Strong understanding of RAG, embeddings, vector databases, and prompt engineering.
- Experience with vector databases such as FAISS, Pinecone, Chroma, Weaviate, or Azure AI Search.
- Experience developing REST APIs using FastAPI/Flask.
- Good understanding of Machine Learning, NLP, and deep learning concepts.
- Experience with Azure / AWS / GCP cloud platforms.
Good to Have
- Experience with multi-agent systems and agent orchestration.
- Knowledge of MLOps / LLMOps.
- Experience with Docker, Kubernetes, and CI/CD.
- Knowledge of LLM evaluation, monitoring, observability, and AI governance.
- Experience with Azure OpenAI, Azure AI Foundry, or AWS Bedrock.
Job Description – Python & Generative AI Engineer
Python & Generative AI Engineer
Location: Bangalore, India
Experience: 4+ Years
Employment Type: Full-time
Job Summary
We are looking for an experienced Python & Generative AI Engineer with 4+ years of software development experience and strong hands-on expertise in Python, LLMs, Generative AI, and AI application development.
The ideal candidate should be comfortable building production-grade AI solutions, integrating LLMs with enterprise applications, and developing scalable APIs and services using Python.
Key Responsibilities
- Design, develop, and deploy Generative AI applications using Python and modern AI/ML frameworks.
- Work with Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, or similar models.
- Develop RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.
- Build AI-powered applications using frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent.
- Develop scalable REST APIs and backend services using FastAPI, Flask, or Django.
- Integrate LLM APIs, prompt engineering, function/tool calling, and structured outputs into enterprise applications.
- Work with vector databases such as FAISS, Pinecone, Weaviate, Milvus, or Azure AI Search.
- Implement document processing, chunking, embeddings, semantic search, and knowledge retrieval solutions.
- Evaluate LLM responses for accuracy, relevance, hallucination, latency, and cost.
- Build and maintain production-ready AI pipelines with appropriate monitoring, logging, security, and error handling.
- Collaborate with data scientists, ML engineers, software engineers, and business stakeholders to deliver AI solutions.
- Write clean, reusable, testable, and well-documented Python code.
- Participate in architecture discussions, code reviews, testing, deployment, and production support.
Required Skills
- 4+ years of experience in software/Python development.
- Strong proficiency in Python and object-oriented programming.
- Hands-on experience with Generative AI and LLM-based applications.
- Experience with OpenAI/Azure OpenAI, Anthropic, Google Gemini, or open-source LLMs.
- Strong understanding of Prompt Engineering and LLM application patterns.
- Experience implementing RAG pipelines.
- Knowledge of embeddings, vector databases, semantic search, and document retrieval.
- Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
- Strong experience developing REST APIs using FastAPI/Flask/Django.
- Familiarity with Git, CI/CD, Docker, and cloud platforms such as AWS, Azure, or GCP.
- Good understanding of SQL and databases.
- Strong problem-solving and communication skills.
Good to Have
- Experience with AI agents / Agentic AI and tool/function calling.
- Experience with multi-agent frameworks.
- Knowledge of MLOps/LLMOps and model evaluation.
- Experience with Kubernetes and containerized deployments.
- Knowledge of NLP, machine learning, or deep learning.
- Experience with Azure AI, AWS Bedrock, Amazon SageMaker, or Google Vertex AI.
- Understanding of responsible AI, data privacy, and LLM security.
Education
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Senior Generative AI Engineer
Employment Type: Permanent with VDart Digital
Work Location: Marathalli, Bengaluru
Job Description
We are seeking a highly skilled Senior Generative AI Engineer with strong expertise in designing, developing, and deploying enterprise-scale AI solutions using Large Language Models (LLMs) and modern Generative AI frameworks. The ideal candidate should have hands-on production experience building scalable GenAI applications, AI agents, autonomous workflows, and Retrieval-Augmented Generation (RAG) systems in cloud-native environments.
This role requires deep technical expertise in LLM orchestration, AI application architecture, prompt engineering, vector databases, MLOps, and production deployment of AI systems. Candidates should have proven experience delivering real-world AI solutions in enterprise environments with strong exposure to cloud platforms and DevOps practices.
Key Responsibilities
- Design, build, and deploy enterprise-grade Generative AI applications using Large Language Models (LLMs).
- Develop intelligent AI agents and autonomous workflows using frameworks such as LangChain, CrewAI, LangGraph, AutoGen, or similar agentic AI frameworks.
- Implement and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic search technologies.
- Work extensively on prompt engineering, tool calling, memory management, agent orchestration, and multi-agent systems.
- Integrate and manage LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or similar foundation models.
- Develop scalable AI services and APIs using Python and FastAPI.
- Build production-ready AI solutions with high availability, scalability, monitoring, and observability.
- Deploy and manage AI applications in cloud-native environments using Docker and Kubernetes.
- Collaborate with Data Science, ML Engineering, and DevOps teams to operationalize AI solutions.
- Implement CI/CD pipelines and automated deployment processes for AI workloads.
- Monitor model performance, latency, reliability, and operational efficiency in production environments.
- Ensure AI solutions follow enterprise security, governance, and responsible AI standards.
- Evaluate and adopt emerging Generative AI tools, frameworks, and models.
Required Skills
Generative AI & LLM Expertise
- Strong hands-on experience with Generative AI and Large Language Models (LLMs).
- Production-level experience building and deploying GenAI applications.
- Expertise in LangChain, CrewAI, LangGraph, AutoGen, or similar frameworks.
- Experience with AI agents, autonomous workflows, and multi-agent architectures.
- Strong understanding of prompt engineering, embeddings, model evaluation, and LLM orchestration.
- Experience integrating OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or similar models.
RAG & Vector Databases
- Strong experience implementing RAG pipelines and semantic retrieval systems.
- Experience with vector databases such as Pinecone, Weaviate, ChromaDB, FAISS, or Milvus.
- Understanding of chunking strategies, embeddings, indexing, reranking, and retrieval optimization.
Python & AI Development
- Strong proficiency in Python.
- Experience with FastAPI for AI service and API development.
- Experience with AI/ML libraries and data processing tools such as Pandas and NumPy.
Cloud & Production Deployment
- Mandatory production experience on at least one cloud platform:
- Microsoft Azure
- Experience deploying scalable AI applications in enterprise production environments.
- Hands-on experience with Docker, Kubernetes, Jenkins, Terraform, and CI/CD pipelines.
- Strong understanding of MLOps, AI deployment lifecycle, monitoring, and observability.
Engineering & Operational Excellence
- Strong understanding of software engineering best practices.
- Experience with Git, version control, automated testing, and release management.
- Experience building secure, scalable, and high-performance AI solutions.
- Ability to troubleshoot production AI systems and optimize performance.
Preferred Skills
- Experience with AI observability and evaluation frameworks.
- Exposure to fine-tuning, PEFT, LoRA, or model optimization techniques.
- Experience with enterprise AI governance and responsible AI practices.
- Knowledge of distributed AI systems and scalable inference architectures.
- Familiarity with AI security and compliance standards.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 3–8 years of overall software engineering experience.
- Minimum 3+ years of hands-on experience in Generative AI and LLM-based application development,
- Proven track record of delivering enterprise-scale AI solutions in production environments.
- Strong communication and stakeholder management skills.
Strong AI Engineer / Machine Learning Engineer profiles.
2
Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.
3
Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.
4
Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.
5
Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.
6
Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.
7
Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.
8
Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.
9
Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.
10
Mandatory (Age) - Candidate's Age should be below 28 Years
Role: AI Developer
Experience: 3–4 Years
Employment Type: Full-Time
Location: Goregaon, Mumbai
About the Role
We are looking for an experienced AI Developer with 3–4 years of software development experience and strong hands-on exposure to Generative AI, AI Agents, Copilots, and AI-powered application development.
The candidate will be responsible for building production-ready AI solutions, developing agentic workflows, modernizing legacy applications, and integrating LLM capabilities into enterprise applications.
Key Responsibilities
- Design, develop, and deploy AI Agents and agentic workflows for enterprise use cases.
- Build AI Copilots and LLM-powered applications using modern AI frameworks and APIs.
- Develop RAG-based applications using embeddings, vector databases, and enterprise data.
- Work on legacy application migration and modernization, leveraging AI-assisted development and code transformation techniques.
- Analyze legacy codebases and design strategies for AI-driven migration, refactoring, and modernization.
- Integrate LLMs with enterprise applications, APIs, databases, and third-party systems.
- Implement tool calling, function calling, multi-agent workflows, and workflow automation.
- Perform prompt engineering, context optimization, model evaluation, and AI application testing.
- Take ownership of AI solutions from POC and prototyping through production deployment.
- Collaborate with product managers, architects, and engineering teams to convert business requirements into scalable AI solutions.
- Stay updated with emerging technologies in Generative AI, Agentic AI, LLMs, and AI-assisted software development.
Required Skills
- 3–4 years of professional software development experience.
- Strong proficiency in Python and/or JavaScript/TypeScript.
- Hands-on experience developing Generative AI / LLM-based applications.
- Strong understanding of AI Agents, RAG, Prompt Engineering, LLM APIs, and embeddings.
- Experience with frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent.
- Experience working with REST APIs, databases, Git, and cloud environments.
- Hands-on experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, or equivalent.
- Good understanding of software architecture, debugging, testing, and deployment practices.
Good to Have
- Experience with Microsoft Copilot / Copilot Studio.
- Experience working with Claude, OpenAI, Gemini, Azure OpenAI, or open-source LLMs.
- Experience in legacy application migration, modernization, or code conversion.
- Knowledge of Azure AI / AWS / Google Cloud AI services.
- Experience with MCP, multi-agent systems, tool calling, and AI orchestration.
- Experience building enterprise-grade AI solutions with focus on security, scalability, and performance.
Experience - 4 to 6 year
Location – Ahmedabad/Pune/Indore
- Additional Job Description
Additional Job Description
Required Skills and Experience:
- Strong proficiency in Python and experience with ML/AI libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face ecosystem).
- Hands-on experience with LLMs, RAG, vector databases, and retrieval pipelines.
- Practical experience deploying agentic workflows and building multi-step, tool-enabled agents.
- Experience using Garak (or similar LLM red-teaming/vulnerability scanners) to identify model weaknesses and harden deployments.
- Demonstrated experience implementing content filtering / moderation systems.
- Solid skills working with structured and unstructured data and advanced feature engineering.
- Familiarity with cloud GenAI platforms and services (Azure AI Services preferred; AWS/GCP acceptable).
- Experience building APIs/microservices; containerization (Docker), orchestration (Kubernetes).
- Strong understanding of model evaluation, performance profiling, inference cost optimization, and observability.
- Good knowledge of security, data governance, and privacy best practices for AI systems.
Hiring for AI Engineer
Exp: 6 - 12 yrs
Edu : BE/B.Tech/MCA
Work Location : Pune / Mumbai
Skill Set:
Total experience ranging from 5–10 years in software engineering/AI roles
Min 5 years strong programming experience in Python or Typescript is a MUST
Min 2.5 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks
2+ years shipping LLM systems in production
Experience with cloud platforms (AWS/Azure/GCP)

Job Summary
We are looking for an experienced AI/ML Engineer to design, develop, deploy, and maintain machine learning and AI solutions that address complex business problems. The ideal candidate should have strong hands-on experience in Python, Machine Learning, Generative AI, LLMs, and AI/ML deployment, with the ability to work across the complete AI/ML lifecycle.
Key Responsibilities
- Design, develop, and deploy scalable Machine Learning and AI models for real-world business use cases.
- Build and optimize ML pipelines covering data preparation, feature engineering, model development, evaluation, and deployment.
- Develop solutions using Generative AI, Large Language Models (LLMs), NLP, and deep learning.
- Work with LLMs, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG) architectures.
- Integrate AI/ML models with enterprise applications and APIs.
- Fine-tune and evaluate ML/LLM models based on business requirements.
- Implement MLOps practices for model versioning, deployment, monitoring, and continuous improvement.
- Collaborate with Data Scientists, Software Engineers, Architects, Product Managers, and business stakeholders.
- Conduct model performance evaluation, optimization, and troubleshooting.
- Ensure AI solutions meet requirements around security, scalability, reliability, responsible AI, and data privacy.
- Stay current with emerging AI/ML technologies, frameworks, and industry best practices.
Required Skills
- Strong programming experience in Python.
- Strong understanding of Machine Learning algorithms, statistics, and data structures.
- Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent.
- Experience with Generative AI and LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, or open-source models.
- Strong knowledge of Prompt Engineering, RAG, embeddings, vector databases, and AI agents.
- Experience with NLP, deep learning, or computer vision is an advantage.
- Experience developing and consuming REST APIs and microservices.
- Working knowledge of SQL and NoSQL databases.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Understanding of Docker, Kubernetes, CI/CD, and MLOps.
- Familiarity with Git and modern software development practices.
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
- 4 years of relevant experience in AI/ML engineering or a related field.
- Experience building and deploying production-grade AI/ML solutions.
- Enterprise application development experience.
- Experience with Azure OpenAI, AWS Bedrock, Vertex AI, or similar managed AI platforms.
- Experience with LangChain, LlamaIndex, Semantic Kernel, or comparable AI frameworks is a plus.
- Experience with AI/ML model monitoring, evaluation, and optimization.
What You Bring
- Strong problem-solving and analytical skills.
- Ability to translate business requirements into practical AI/ML solutions.
- Strong software engineering and debugging capabilities.
- Ability to work independently as well as collaboratively in a cross-functional environment.
- Good communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders.
Keywords
AI Engineer | ML Engineer | Machine Learning | Generative AI | LLM | Python | NLP | Deep Learning | RAG | Prompt Engineering | AI Agents | Azure OpenAI | AWS Bedrock | MLOps | TensorFlow | PyTorch | Scikit-learn | Vector Database | Cloud AI
Location: Gurugram
Work mode: Hybrid










