Senior AI Engineer at Daivtech Solutions Pvt Ltd · Bengaluru (Bangalore) · 5 - 10 years · ₹10L - ₹20L / yr · Posted 20 Oct 2026
Flask
Django
Deep LearningJob Title: Senior AI Engineer
Experience: 5–10 years in software engineering, with 3+ years in AI/ML engineering preferred
Employment Type: Full-time
Department: Artificial Intelligence / Engineering
Location: Bangalore
We are looking for a highly skilled Senior AI Engineer to design, develop, deploy, and scale intelligent AI-powered applications and solutions. The ideal candidate will have strong expertise in machine learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and production-grade software engineering.
The candidate will work closely with product managers, data scientists, software engineers, and business stakeholders to translate complex business requirements into scalable, reliable, secure, and cost-effective AI solutions.
Key Responsibilities
1. AI Solution Design and Development
- Design, develop, and deploy end-to-end AI and machine learning solutions.
- Build intelligent applications using LLMs, Generative AI, NLP, and deep learning techniques.
- Develop scalable AI architectures and reusable components for enterprise applications.
- Evaluate AI models and select appropriate approaches based on accuracy, latency, cost, and business requirements.
2. Generative AI and LLM Engineering
- Develop LLM-powered applications using models from providers such as OpenAI, Anthropic, Google, or open-source ecosystems.
- Design and implement RAG pipelines, document processing workflows, semantic search, and knowledge retrieval systems.
- Build AI agents and multi-step workflows using appropriate orchestration frameworks.
- Implement prompt engineering, structured outputs, tool calling, and context management.
- Optimize model performance through evaluation, fine-tuning where appropriate, and inference optimization.
3. Machine Learning and Data Engineering
- Develop and operationalize machine learning models for classification, prediction, recommendation, and other business use cases.
- Work with structured, unstructured, and multimodal data.
- Build data preprocessing, feature engineering, model training, and validation pipelines.
- Apply appropriate model evaluation techniques and statistical methods.
4. Production Deployment and MLOps / LLMOps
- Deploy AI solutions using cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
- Build automated CI/CD pipelines for AI applications and model deployment.
- Implement model versioning, experiment tracking, monitoring, and performance evaluation.
- Optimize inference latency, throughput, infrastructure utilization, and operating costs.
- Establish observability for AI applications, including token usage, retrieval quality, latency, failures, and model behavior.
5. Software Engineering and System Architecture
- Develop production-quality applications and APIs using Python and modern backend frameworks.
- Design RESTful APIs, asynchronous processing systems, and microservices where appropriate.
- Integrate AI services with enterprise applications, databases, and third-party systems.
- Use relational databases, vector databases, caching, and distributed systems effectively.
- Apply software engineering best practices, including testing, code reviews, documentation, and design patterns.
6. Security, Quality, and Responsible AI
- Implement safeguards against prompt injection, data leakage, insecure tool execution, and unauthorized access.
- Apply appropriate privacy, security, and compliance controls to AI systems.
- Evaluate hallucinations, bias, reliability, and failure modes.
- Design human-in-the-loop workflows and fallback mechanisms for critical use cases.
7. Technical Leadership and Collaboration
- Lead technical design discussions and mentor junior AI engineers.
- Define engineering standards, coding practices, and AI development guidelines.
- Collaborate with cross-functional teams to deliver measurable business outcomes.
- Conduct code reviews, evaluate emerging technologies, and recommend practical innovations.
- Communicate technical trade-offs and solution architecture to both technical and non-technical stakeholders.
Required Technical Skills
Programming and Backend Development
- Strong proficiency in Python.
- Experience with FastAPI, Flask, or Django.
- Knowledge of REST APIs, asynchronous programming, data structures, algorithms, and software design principles.
- Experience with Git, automated testing, and CI/CD.
AI and Machine Learning
- Strong understanding of supervised and unsupervised learning, model evaluation, and statistical concepts.
- Hands-on experience with PyTorch, TensorFlow, or scikit-learn.
- Knowledge of NLP, embeddings, transformers, and deep learning fundamentals.
Generative AI and LLMs
- Hands-on experience building production applications using LLM APIs or open-source models.
- Strong understanding of RAG architecture, embeddings, chunking, reranking, and retrieval evaluation.
- Experience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, or pgvector.
- Familiarity with orchestration frameworks such as LangChain, LangChain, or comparable tools.
- Experience with tool calling, structured generation, agent workflows, and LLM evaluation.
Cloud and Infrastructure
- Experience with AWS, Azure, or Google Cloud.
- Working knowledge of Docker and Kubernetes.
- Familiarity with model serving, scalable APIs, monitoring, and production deployments.
- Experience with MLOps or LLMOps practices.
Databases and Data Processing
- Strong SQL skills and experience with relational databases.
- Familiarity with NoSQL databases, data pipelines, and distributed processing.
- Experience working with unstructured data, document ingestion, and retrieval systems.
Preferred Qualifications
- Experience with fine-tuning, quantization, or serving open-source LLMs.
- Experience with multimodal AI, including text, image, audio, or video.
- Knowledge of agent evaluation, workflow orchestration, and multi-agent systems.
- Experience with AI security, guardrails, governance, and responsible AI.
- Experience optimizing AI workloads for latency, scalability, and cost.
- Contributions to open-source AI projects, research, or technical publications.
Education
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
- Equivalent practical experience and demonstrated engineering expertise may be considered.
Key Success Metrics
- Quality, accuracy, and reliability of deployed AI solutions.
- Production adoption and measurable business impact.
- Reduction in inference costs and response latency.
- RAG retrieval quality and reduction in unsupported or incorrect responses.
- System availability, scalability, and operational stability.
- Delivery timelines, code quality, and technical mentoring effectiveness.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Daivtech Solutions Pvt Ltd
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Hiring for AI Engineer
Exp: 5 - 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)
Python
Machine Learning (ML)Principal Software Engineer
Company Summary :
As the recognized global standard for project-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values-driven environment, where every employee feels included and empowered to do their best work. Our employees put our core values into action daily, creating a one-of-a-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America's Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress. www.deltek.com
Position Responsibilities :
About the Role
We are seeking a highly motivated AI Solutions Engineer to join Deltek’s growing AI Center of Excellence team to design, develop, deploy, and optimize internal Artificial Intelligence and Machine Learning solutions that solve complex business challenges. The ideal candidate combines deep expertise in AI, machine learning, Generative AI, Large Language Models (LLMs), SLMs, software engineering, cloud computing, and MLOps/LLMOps to build scalable, production-grade AI applications.
The AI Solutions Engineer will collaborate with AI data scientists, architects, and engineering teams to deliver innovative AI-driven solutions while ensuring security, scalability, governance, and operational excellence. This role reports to the Senior AI Solutions Architect.
Key Responsibilities
AI & Machine Learning Development
- Design, build, train, evaluate, and deploy machine learning and deep learning models.
- Develop Generative AI solutions using Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, and Mistral.
- Implement Retrieval-Augmented Generation (RAG), prompt engineering, fine-tuning, and AI agent frameworks.
- Build NLP, recommendation systems, forecasting, predictive analytics, and intelligent automation solutions.
- Optimize model performance, scalability, latency, and cost.
Software Engineering & Solution Development
- Develop production-grade AI applications using Python and modern software engineering practices.
- Build APIs, microservices, and AI-powered enterprise applications.
- Integrate AI services with enterprise systems, business applications, and data platforms.
- Apply coding standards, automated testing, CI/CD, and version control best practices.
MLOps & AI Operations
- Design and implement MLOps pipelines for model development, deployment, monitoring, and lifecycle management.
- Automate model training, validation, testing, and deployment processes.
- Monitor model performance, data drift, hallucinations, and operational metrics.
- Support continuous improvement and reliability of AI platforms.
Cloud & Platform Engineering
- Develop AI solutions on Azure, AWS, or Google Cloud platforms.
- Leverage cloud-native AI services, containerization, Kubernetes, and serverless technologies.
- Build scalable architectures supporting enterprise AI workloads and real-time inference.
AI Governance & Security
- Ensure compliance with Responsible AI, security, privacy, and regulatory requirements.
- Implement model governance, explainability, bias mitigation, and risk management practices.
- Maintain standards for secure design, deployment, and operation of AI solutions.
Required Qualifications
Education
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related technical field.
Experience
- 5+ years of software engineering or machine learning development experience.
- 2+ years of hands-on experience developing and deploying Agentic AI, Generative AI or AI/ML solutions in production environments.
Technical Skills
Programming & Engineering
- Strong expertise in Python.
- Experience with Java, ReactJS, JavaScript, or similar programming languages.
- Solid understanding of algorithms, data structures, APIs, and software design principles.
Artificial Intelligence & Machine Learning
- Machine Learning and Deep Learning concepts and frameworks.
- Model training, evaluation, optimization, and deployment.
Generative AI
- Large Language Models (LLMs) & SLMs
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Agents and Agentic Workflows
- Fine-tuning and model customization
- Vector embeddings and semantic search
Frameworks & Tools
- PyTorch, TensorFlow, Scikit-learn
- LangChain, LlamaIndex, Semantic Kernel, MCP, A2A and Transformers
- FastAPI, Flask
Data & Analytics
- SQL and NoSQL databases
- Data pipelines, ETL, and data modeling
- Experience with AWS, Azure and Google
MLOps & DevOps
- MLflow, Kubeflow, Azure ML, SageMaker
- Docker and Kubernetes
- Git, GitHub, Azure DevOps, Jenkins
- CI/CD automation and model monitoring
Cloud Platforms
- AWS (preferred)
- AWS Bedrock or Azure OpenAI Service
- AWS SageMaker
- Google Vertex AI
Preferred Qualifications
- Experience designing enterprise-scale AI platforms and products.
- Knowledge of multi-agent architectures and autonomous AI systems.
- Experience with vector databases such as Pinecone, Snowflake Cortex, Pgvector, Weaviate, Chroma, or Azure AI Search.
- Understanding of AI governance, compliance, and Responsible AI frameworks.
- Relevant certifications in Azure AI, AWS Machine Learning, or Google Cloud AI.
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
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.
Amazon Web Services (AWS)PythonJob 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
Machine Learning (ML)Python
JavascriptHiring for Junior AI Engineer
Exp : 4 - 6 yrs
Edu : BE/B.Tech/MCA
Work Location : Pune WFO
Skills :
- Min 3 years strong programming experience in Python is a MUST
- Min 2 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks
- Experience with cloud platforms (AWS/Azure/GCP)
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.
Machine Learning (ML)Deep LearningPython🚀 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
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
PythonDjangoMust of Skills/Experience
• System Design
• Python
• TensorFlow
• Google ADK or Lang Graph
• Lang Chain , Lang Graph
• Spark
• Agentic AI Design
• ML Ops
• MCP (client and server)
• FastAPI
• Doc Factory
• RAG
• Golang
• LLMs – Gemini, Open AI
• NLP
• Dev Assistant - AI based code - generation
(Qwen or Claude or Copilot)
• CI/CD
• Good in oral and written communication,
collaboration and be a team player
Good to have skills
• DevOps with K8
• Scripting
• Java
• REST API
• UV
• ReACT
• DocFactory
• Unix
- Senior Machine Learning Engineer – Vertex AI
- Senior Generative AI Engineer – GCP
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Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon