Full Stack AI Developer at UpSolve Solutions LLP · Mumbai · 0 - 3 years · ₹2L - ₹3.5L / yr · Bootstrapped · Posted 7 Feb 2026

Role Description
We are seeking a full-time AI Developer specializing in Generative AI and Large Language Models (LLMs) to join UpSolve Solutions in Mumbai. This client-facing, on-site role involves designing, developing, and deploying AI models, specifically focusing on GenAI and LLMs. The AI Developer will leverage expertise in machine learning, natural language processing, and data science to build cutting-edge AI solutions that drive business innovation and solve complex challenges.
Qualifications
- Proficiency in Python
- Strong projects in Flask + JS
- Excellent problem-solving, critical thinking, and analytical skills
- Strong communication and presentation skills, with the ability to convey technical concepts to non-technical stakeholders
- Bachelor's or Master’s degree in a relevant field (e.g., Computer Science, Artificial Intelligence, Data Science)

About UpSolve Solutions LLP
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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.
Hiring for AI Engineer
Exp: 5 - 8 yrs
Edu : BE/B.Tech/MCA
Work Location : Pune
Skill Set:
Total experience ranging from 5 - 8 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
Experience with cloud platforms (AWS/Azure/GCP)
🚀 Hiring: Python + Gen AI Developer
📍 Location: Bengaluru
💼 Experience: 4–6 Years
Mandatory Skills:
✅ Python
✅ Generative AI / Gen AI
✅ LLMs / AI Application Development
✅ Python Backend / API Development
Role:
Looking for a skilled Python + Gen AI Developer with hands-on experience in developing Python-based applications and integrating Generative AI/LLM solutions.
🔹 Develop scalable Python applications
🔹 Build and integrate Gen AI/LLM solutions
🔹 Develop APIs and backend services
🔹 Collaborate with cross-functional teams
🔹 Troubleshoot and optimize applications
📩 Interested candidates can share their updated resume.
#Hiring #PythonDeveloper #GenAI #GenerativeAI #LLM #AIJobs #BengaluruJobs #TechHiring #ITJobs
Job Title: Python + GenAI Developer
Experience: 4–6 Years
Location: Bangalore / Hyderabad (as applicable)
Job Description:
We are looking for a skilled Python + Generative AI Developer with hands-on experience in Python development, LLM integration, and building AI-powered applications.
Key Responsibilities:
- Develop backend applications and REST APIs using Python.
- Build and integrate Generative AI solutions using LLMs.
- Work with frameworks such as LangChain or LangGraph.
- Implement Retrieval-Augmented Generation (RAG) pipelines and vector databases.
- Integrate OpenAI or other LLM APIs into applications.
- Collaborate with teams to develop, test, and deploy AI-powered solutions.
- Work with cloud platforms such as AWS, Azure, or GCP.
Required Skills:
- 4–6 years of Python development experience.
- Hands-on experience with Generative AI and LLMs.
- Experience with LangChain or LangGraph.
- Knowledge of RAG and vector databases.
- Experience developing REST APIs using FastAPI or Flask.
- Understanding of prompt engineering and LLM integration.
- Familiarity with Git and cloud platforms.
Preferred Skills:
- Experience with Agentic AI and AI agents.
- Knowledge of embeddings and semantic search.
- Experience with Docker and CI/CD.
We are seeking Generative AI Developers with strong Python programming and AI/ML expertise to build, deploy, and optimize LLM-powered applications. The role involves developing RAG solutions, AI agents, and enterprise GenAI applications while collaborating with cross-functional teams.
Key Responsibilities
- Develop and enhance Generative AI applications using LLMs and AI frameworks.
- Build and optimize RAG pipelines, vector search, and AI-powered workflows.
- Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA.
- Develop REST APIs and integrate AI capabilities into enterprise applications.
- Deploy, monitor, and maintain AI solutions in cloud and containerized environments.
- Ensure code quality through testing, debugging, documentation, and code reviews.
- Follow Responsible AI, security, and data governance practices.
Required Technical Skills
- Strong proficiency in Python, OOP, APIs, debugging, and software development best practices.
- Good understanding of Data Structures & Algorithms, complexity analysis, and problem-solving.
- Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings.
- Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar frameworks.
- Knowledge of vector databases, semantic/hybrid search, and retrieval architectures.
- Experience with PyTorch, TensorFlow, or Keras.
- Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP).
- Understanding of AI governance, data privacy, and Responsible AI principles.
Preferred Skills
- Experience with Agentic AI frameworks (CrewAI, AutoGen, Semantic Kernel).
- Exposure to Azure AI Foundry, Databricks, or enterprise AI platforms.
- Knowledge of multimodal AI applications.
Qualifications
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
- 5 years of software development experience, including AI/ML or Generative AI projects.
- Experience building and deploying production-grade AI solutions.
Assessment Focus Areas
Candidates will be evaluated on:
- Python coding and problem-solving
- Data Structures & Algorithms
- LLMs, RAG, and Agentic AI concepts
- API development and system design
- Cloud deployment and AI solution architecture
AI Developer
Primary Skill-set (Must have)
- Generative AI Expertise: 2-3 years of experience in designing and implementing generative AI solutions, including knowledge of various generative and autoregressive models. Ability to apply generative AI techniques to diverse use cases such as image generation, text generation, and creative content synthesis.
• 2 years of experience in prompt engineering, fine tuning, agentic framework, GenAI SDK’s
• 1-2 years of experience in Agentic AI frameworks like Autogen, Lanngraph, MS Agent SDK, A2A, MCP, A2P, memory concepts, multi agent orchestration
• 7+ years of experience in Python
• 5+ years of experience in software development
• Azure Proficiency: 3-5 years of experience with Azure cloud services relevant to AI, including Azure Machine Learning, Azure Cognitive Services, Azure Databricks, and Azure Kubernetes Service (AKS). 2+ years of experience in Azure's capabilities to architect end-to-end AI solutions and optimize performance.
• Architecture Design: 3-5 years of skills with the ability to design scalable, reliable, and cost-effective architectures for AI solutions. Proficiency in designing distributed systems, microservices architectures, and containerized solutions using technologies such as Docker and Kubernetes.
Secondary Skills (Good to have)
• Security and Compliance: Understanding of security principles and best practices in AI development, with the ability to implement security controls, encryption mechanisms, and access management policies to protect AI models and sensitive data.
• Integration and Deployment: Proficiency in implementing CI/CD pipelines, automation scripts, and infrastructure as code (IaC) using tools such as Azure DevOps, Terraform, or Ansible. Experience in containerization and orchestration of AI workloads using Docker and Kubernetes.
• Software Development: Strong programming skills in languages such as Python, with experience in developing AI applications, RESTful APIs, and microservices architectures. Familiarity with software development methodologies such as Agile or Scrum.
• Communication and Presentation: Excellent communication skills with the ability to convey complex technical concepts to non-technical stakeholders. Experience in preparing and delivering technical presentations, architecture diagrams, and documentation to communicate architectural decisions and design rationale effectively.
Dear Candidate,
Thanks for showing interest towards the opportunity!!!
As discussed, we have an immediate opening for Python + Agentic AI Developer with Mphasis for Bangalore location.
Experience: 4 Years
Mandatory Skills: Python, Agentic AI, Generative AI (GenAI), LLMs, AI Agents.
Kindly share your updated resume and availability for the opportunity.
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.
Job 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.
🚀 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










