Senior AI Engineer

About the Role

We are looking for an AI/ML Engineer with 4+ years of Strong hands-on experience building and deploying production-grade AI systems. The ideal candidate should have strong expertise in Computer Vision, Generative AI, RAG pipelines, Voice AI, and LLM-powered applications, with experience delivering scalable, production-ready solutions across enterprise, healthcare, or SaaS environments

Key Responsibilities

• Design, develop, and deploy production-ready AI/ML and Generative AI applications, Computer Vision solutions.
• Build and optimize LLM-powered applications for real-world business use cases.
• Develop and maintain RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.
• Build Voice AI solutions including speech-to-text (STT), text-to-speech (TTS), conversational AI, and voice-enabled assistants.
• Create and optimize prompt engineering strategies to improve LLM output quality, consistency, and reliability.
• Work with open-source LLMs for inference, fine-tuning, evaluation, and deployment.
• Implement model monitoring, evaluation, guardrails, and performance optimization.
• Collaborate with DevOps and cloud teams for scalable deployments.
• Optimize AI systems for latency, cost, scalability, and production performance.
• Integrate AI services through APIs and enterprise applications.

Required Skills & Experience

• 4+ years of experience in AI/ML engineering and production deployments.
• Strong experience in Python and AI/ML development.
• Hands-on experience with Generative AI and LLM applications.
• Strong hands-on experience in Computer Vision using Python and frameworks such as OpenCV, PyTorch, and TensorFlow.
• Experience with Computer Vision tasks such as object detection, image classification, image segmentation, and feature extraction.
• Familiarity with models and libraries such as YOLO, Detectron2, MMDetection, and torchvision.
• Experience with image preprocessing, data augmentation, model training, evaluation, and inference optimization.
• Exposure to OCR technologies such as Tesseract or EasyOCR and vision-based deep learning models is an advantage.
• Experience building RAG pipelines using:
• Vector Databases: Pinecone, Weaviate, FAISS, ChromaDB, Milvus
• Embeddings and retrieval optimization
• Experience with Prompt Engineering techniques for LLM optimization.
• Experience with Open Source LLMs such as:
• Llama, Mistral, Falcon, Gemma, DeepSeek, Qwen
• Experience with Voice AI technologies:
• Speech-to-Text (Whisper, Deepgram, Google STT)
• Text-to-Speech (ElevenLabs, Azure Speech, Amazon Polly)
• Conversational Voice Agents
• Experience using frameworks/tools:
• LangChain, LangGraph, LlamaIndex, Hugging Face
• Understanding of fine-tuning, model evaluation, inference optimization, and AI observability.
• Experience deploying applications using:
• Docker, Kubernetes, CI/CD
• AWS / Azure / GCP

Preferred Qualifications

• Experience delivering AI solutions for Healthcare, Enterprise, or SaaS platforms.
• Exposure to MLOps practices and model lifecycle management.
• Understanding of AI governance, security, and responsible AI practices.
• Experience integrating AI with APIs and production services.

Nice to Have

• Knowledge of agentic AI workflows and orchestration.
• Experience with monitoring and evaluation frameworks.
• Exposure to multimodal AI applications

Education Qualifications

• B.Tech / M.Tech in CSE / IT / AI&ML only from good college.

Immediate Joiner - 15 days Notice period

• Primary Skillsets: Python, Generative AI, Agentic AI, LLM, experience with designing and developing production grade AI solutions, AWS/Azure/GCP, LLMOps, Data Engineering (Databricks/Snowflake), Regulated GenAI, Data and Decisions, and Agentic Systems.

• Preferred: Pharma or life sciences experience, especially in regulated (GxP) environments, experience setting up a team or practice from scratch.

Kody Technolab Limited is seeking an experienced AI/ML Engineer to design, develop, and deploy cutting-edge Artificial Intelligence and Machine Learning solutions. The ideal candidate will have

strong expertise in Machine Learning, Deep Learning, Generative AI, LLMs, MLOps, and cloud-based AI deployments.

Key Responsibilities

• Design, develop, and deploy Machine Learning and Deep Learning models for classification, regression, recommendation systems, NLP, Computer Vision, and Generative AI applications.

• Build and maintain end-to-end ML pipelines including data preprocessing, feature engineering, model training, validation, evaluation, and deployment.

• Develop AI solutions using PyTorch, TensorFlow, Scikit-learn, Hugging Face, and related frameworks.

• Work with Large Language Models (LLMs) and foundation models such as GPT, BERT, Llama, Claude, and Stable Diffusion.

• Collaborate with product, engineering, and business teams to translate requirements into scalable AI solutions.

• Optimize model performance, scalability, and reliability for production environments.

• Implement MLOps best practices using tools such as MLflow, Docker, Kubernetes, and Kubeflow.

• Stay updated with emerging trends and research in AI, ML, Deep Learning, and Generative AI.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field.

• 7+ years of hands-on experience in AI/ML product development.

• Strong proficiency in Python and ML frameworks including Scikit-learn, TensorFlow, PyTorch, and Hugging Face.

• Experience with Generative AI, LLMs, GANs, VAEs, diffusion models, and prompt engineering.

• Strong understanding of the ML lifecycle including model training, tuning, deployment, monitoring, and optimization.

• Experience with MLOps tools such as MLflow, Docker, Kubeflow, and CI/CD pipelines.

• Experience with AWS, Azure, or GCP cloud platforms.

• Strong problem-solving and analytical skills.

Preferred Skills

• Fine-tuning and deployment of Large Language Models.

• Experience with RAG (Retrieval Augmented Generation) architectures.

• Contributions to open-source AI projects or research publications.

• Knowledge of model interpretability, data annotation, and feature engineering.

• C++ experience for high-performance AI applications.

Why Join Kody Technolab Limited?

Opportunity to work on innovative AI products, Generative AI solutions, robotics integrations,

and enterprise-scale applications while collaborating with a highly skilled technology team.

Visit the Website to know more about us.

Company Website - Kody Technolab | Deep Tech Company in Robotics & AI Solution

Kody Robots | Robotics Company in India for Autonomous Robots

AI Engineer

Experience: 2–4 Years

Employment Type: Full-Time

Work Mode: Coimbatore / Hybrid

About Techjays

Techjays is an AI Reimagination Company focused on building intelligent, scalable, and impactful software solutions. We help businesses solve complex challenges through AI, automation, and modern software engineering.

We are looking for an AI Engineer who is passionate about building AI-powered applications and integrating modern AI technologies into real-world products.

Key Responsibilities

• Design, develop, and deploy AI-powered applications using Python and modern AI frameworks.
• Build and implement LLM-based applications, including Retrieval-Augmented Generation (RAG) systems.
• Work with LLM APIs such as OpenAI, Gemini, and Anthropic.
• Develop AI agents and workflows using frameworks such as LangChain and LangGraph.
• Integrate vector databases and implement efficient embedding and semantic search solutions.
• Develop scalable backend services and REST APIs.
• Work with databases, data processing pipelines, and cloud-based services.
• Collaborate with frontend and backend teams to integrate AI capabilities into applications.
• Evaluate AI model performance, improve response accuracy, and optimize application performance.
• Debug, test, and maintain production-grade AI applications.

Required Skills

• 2–4 years of experience in software development, AI engineering, or a related field.
• Strong programming knowledge in Python.
• Hands-on experience with LLMs and Generative AI applications.
• Understanding of RAG architecture, embeddings, and semantic search.
• Experience with frameworks such as LangChain, LangGraph, or LlamaIndex.
• Knowledge of vector databases such as Pinecone, FAISS, ChromaDB, or Qdrant.
• Experience in building REST APIs using FastAPI or Flask.
• Good understanding of SQL and NoSQL databases.
• Familiarity with Git, Docker, and basic cloud services.
• Strong problem-solving and analytical skills.

Good to Have

• Experience building AI agents and multi-agent systems.
• Knowledge of React or other frontend frameworks.
• Exposure to AWS, Azure, or GCP.
• Understanding of model evaluation, prompt engineering, and fine-tuning.
• Experience deploying AI applications in production environments.

What We’re Looking For

• Someone who enjoys solving real-world problems using AI.
• Ability to take ownership of tasks and deliver solutions independently.
• Strong learning mindset and willingness to explore emerging AI technologies.
• Good communication and collaboration skills.

Job Details

Position Title: AI Evangelist

Role Purpose

We are seeking a highly experienced AI Evangelist & Core AI Engineer who combines deep technical expertise in Artificial Intelligence with the ability to influence, educate, demonstrate, and accelerate AI adoption across the enterprise.

The role requires deep understanding of AI, Machine Learning, Deep Learning, Generative AI, Large Language Models, Agentic AI, AI engineering, and modern software development practices, combined with significant hands-on experience implementing scalable AI applications in complex enterprise environments.

Key Responsibilities

1. Core AI Engineering & Architecture

• Design, develop, and implement enterprise-grade AI and Generative AI applications.
• Build scalable applications using LLMs, multimodal models, AI agents, RAG, vector databases, knowledge graphs, APIs, and enterprise data platforms.
• Architect AI solutions capable of supporting enterprise-scale workloads with appropriate considerations for:
• Scalability
• Reliability
• Security
• Performance
• Observability
• Cost optimization
• Governance
• Develop and implement advanced Retrieval-Augmented Generation (RAG) architectures including hybrid search, reranking, metadata filtering, semantic retrieval, and knowledge grounding.
• Build multi-agent and agentic AI applications capable of reasoning, tool usage, workflow execution, orchestration, and enterprise system integration.
• Design AI applications integrating structured and unstructured enterprise information.
• Evaluate architecture choices between commercial models, open-source models, small language models, domain-specific models, and hosted AI platforms.
• Implement model routing, prompt orchestration, caching, guardrails, evaluation pipelines, and fallback strategies.
• Work closely with cloud, platform, security, enterprise architecture, DevOps, and application engineering teams.

2. Deep AI / ML / DL Expertise

The candidate should have strong conceptual and practical understanding across the modern AI technology landscape, including:

• Artificial Intelligence /Machine Learning/ Deep Learning/ Neural Networks /LLM/SLM/RAG/Graph RAG / MLOps / LLMOps / GenAIOps

3. Generative AI & LLM Engineering

• Build production-grade applications utilizing leading commercial and open-source LLM ecosystems.
• Design scalable LLM platforms supporting multiple enterprise applications and use cases.
• Develop reusable LLM services, APIs, components, agent frameworks, and reference architectures.

4. AI Agents & Automation

• Design and implement AI agents and agentic workflows that automate complex business and engineering processes.
• Build agents capable of interacting with enterprise applications, APIs, databases, documents, development environments, and workflow platforms.
• Evaluate emerging agent architectures and orchestration frameworks pragmatically.
• Develop reusable patterns for:
• Single-agent systems
• Multi-agent systems
• Human-in-the-loop workflows
• Autonomous workflows
• Tool-calling agents
• Coding agents
• Enterprise knowledge agents
• Establish appropriate controls for AI agent identity, permissions, auditability, security, and human oversight.

5. AI-Enabled Software Engineering

Drive adoption of AI throughout the Software Development Life Cycle.

• Primary Skillsets: Python, Generative AI, Agentic AI, LLM, experience with designing and developing production grade AI solutions, AWS/Azure/GCP, LLMOps, Data Engineering (Databricks/Snowflake), Regulated GenAI, Data and Decisions, and Agentic Systems.
• Preferred: Pharma or life sciences experience, especially in regulated (GxP) environments, experience setting up a team or practice from scratch.
• Only immediate joiners are considered.

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

Role Overview 

We are looking for an AI Engineer to design, build, and ship production AI systems, including agentic AI applications, for enterprise clients. This is a hands-on engineering role: you will write production code, build and evaluate models and agents, and work closely with architects and product teams to take solutions from prototype to scale. 

Key Responsibilities 

Design and build agentic AI systems: agent workflows, tool/function-calling, memory, and human-in-the-loop patterns. Build and productionise RAG pipelines, prompt-based applications, and LLM integrations across providers. Develop and maintain data and ML pipelines: feature engineering, model training, evaluation, and monitoring. Integrate AI systems with enterprise applications (CRMs, ERPs, ITSM tools) via APIs, events, and MCP-based tool servers. Implement guardrails, prompt-injection defences, and evaluation frameworks to keep AI systems safe and reliable in production. 

Write clean, tested, production-grade code and participate actively in code and design reviews. 

Collaborate with architects, product managers, and delivery teams to translate requirements into working AI solutions. Troubleshoot and optimise AI systems for accuracy, latency, and cost in production. 

Required Qualifications 

8–12 years of hands-on software engineering experience, with a strong, unbroken technical track record. Hands-on experience building and shipping AI/ML systems in production, not just POCs. 

Practical experience with agentic AI systems and at least one major agent framework (LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Bedrock Agents/Strands, or Semantic Kernel). 

Experience with LLM/GenAI systems: RAG pipelines, prompt engineering, structured outputs, and tool calling across providers. 

Strong Python skills (TypeScript/Node.js a plus), with production-grade testing, CI/CD, and API design practices. Working knowledge of ML fundamentals: model evaluation, feature engineering, and experimentation. Cloud-native experience on AWS and/or Azure: containers, serverless, event backbones, and vector databases. Understanding of LLM safety and reliability practices: guardrails, prompt-injection defences, and observability. 

Senior AI Engineer

Company: Techjays

Experience: 4–8 Years

Location: Coimbatore, Hybrid

Joining: Immediate or within 30 days preferred

About the Role

We are looking for a Senior AI Engineer with strong Python development skills and hands-on experience building and deploying AI-powered applications. The ideal candidate should have practical knowledge of LLMs, Retrieval-Augmented Generation (RAG), vector databases, and scalable backend systems.

You will work closely with engineering and product teams to design, develop, and deploy reliable AI solutions for real-world business problems.

Key Responsibilities

• Design, develop, and maintain scalable backend applications using Python and frameworks such as Django, Flask, or FastAPI.
• Build and integrate AI-powered applications using LLMs, RAG pipelines, and agentic AI workflows.
• Develop document processing, embedding generation, semantic search, and retrieval pipelines.
• Integrate LLM APIs and optimize prompts, response quality, latency, and cost.
• Work with vector databases and relational databases to build efficient data retrieval systems.
• Design and implement REST APIs, asynchronous processing, caching, and queuing mechanisms.
• Apply software engineering best practices, including design patterns, clean code, testing, and version control.
• Deploy and maintain applications on AWS or GCP using Docker and CI/CD pipelines.
• Monitor production systems, troubleshoot issues, and improve application performance and reliability.
• Collaborate with cross-functional teams to translate business requirements into practical AI solutions.
• Contribute to code reviews, technical documentation, and knowledge sharing within the engineering team.

Required Skills

• 4–8 years of experience in software development, with strong hands-on Python expertise.
• Strong understanding of data structures, algorithms, object-oriented programming, and design patterns.
• Experience building backend applications using Django, Flask, or FastAPI.
• Hands-on experience with LLM-based applications and API integrations.
• Practical experience implementing RAG pipelines, embeddings, and semantic search.
• Experience with vector databases such as Pinecone, Qdrant, Weaviate, or Chroma.
• Strong knowledge of SQL and relational databases such as PostgreSQL or MySQL.
• Experience with caching, message queues, asynchronous processing, and WebSockets.
• Familiarity with AWS or GCP, Docker, Git, and CI/CD pipelines.
• Understanding of API design, system architecture, application security, and performance optimization.
• Experience testing, debugging, and maintaining production-grade applications.

Preferred Skills

• Experience building agentic AI applications and multi-agent workflows.
• Familiarity with LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Knowledge of Model Context Protocol (MCP) and tool-calling mechanisms.
• Experience with LLM evaluation, hallucination reduction, and output quality monitoring.
• Familiarity with fine-tuning, model selection, and inference optimization.
• Experience with LLMOps, AI observability, and production monitoring.
• Knowledge of Kubernetes and microservices architecture.

What We’re Looking For

• Strong problem-solving and analytical skills.
• Ability to take ownership of features from development through deployment.
• Practical understanding of how to build reliable AI applications beyond prototypes.
• Ability to make sound technical decisions and explain architectural trade-offs.
• Good communication and collaboration skills.
• Willingness to learn, experiment, and work on challenging AI engineering problems.

🚀 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