Generative AI Developer at PixelPhant · Udaipur · 3 - 5 years · ₹4L - ₹9L / yr · Profitable · Posted 22 Nov 2023

We are seeking a highly skilled and innovative 3+ years of experienced Generative AI Engineer to join our dynamic team. As a Generative AI Engineer, you will play a key role in developing cutting-edge algorithms and models to create generative solutions that push the boundaries of artificial intelligence.
Key Responsibilities
- Design, develop, and implement cutting-edge computer vision algorithms, encompassing areas such as image processing, object detection, and segmentation.
- Leverage Generative Adversarial Network (GAN) models to synthesize novel data and enhance the quality of existing datasets.
- Engage in collaborative efforts with cross-functional teams to seamlessly integrate AI-driven solutions into our product portfolio.
- Spearhead initiatives to refine and optimize model architectures, ensuring top-tier performance and efficiency.
- Stay at the forefront of AI and computer vision advancements, ensuring our solutions are consistently state-of-the-art.
- Provide mentorship to budding data scientists, promoting a cohesive, inclusive, and knowledge-sharing team culture.
Qualifications:
- A minimum of 3 years of specialized experience in computer vision, with a focus on deep learning. Proficiency in neural architectures such as CNNs, RNNs, Encoder-Decoders, and generative models including GANs and GPT is essential.
- Demonstrated expertise in crafting, fine-tuning, and deploying AI models for real-world applications.
- Mastery in programming languages, notably Python, and familiarity with deep learning frameworks such as TensorFlow and PyTorch. Experience with image processing libraries like OpenCV and Pillow is a plus.
- Exceptional analytical and problem-solving prowess, complemented by meticulous attention to detail.
- Stellar communication and presentation abilities, with a knack for distilling intricate technical data into clear, actionable business insights.
Preferred Skills:
- Hands-on experience with cloud platforms, especially AWS, and adeptness with container orchestration tools like Docker and Kubernetes.
- Proficiency in version control utilities, particularly Git and GitHub.
- Prior contributions to the AI research community, such as publications or significant community involvement, will be highly regarded.
- Acquaintance with agile development practices.
- A compelling portfolio showcasing a range of projects in computer vision and image segmentation is desirable

About PixelPhant
About
About the company: PixelPhant Private Limited is a Professional Product Photo Editing Service provider company we Process 5000+ files each day to help eCommerce businesses scale faster. We are a 6-year-old company based in Udaipur (RAJ.). We are looking to expand fast and are in search of smart people who would love photo editing.
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Job Summary:
Wissen Technology is hiring an AI Implementation Engineer to build, deploy, and scale enterprise-grade Generative AI solutions across business-critical applications. The role involves developing production-ready AI systems using Azure AI services, Large Language Models (LLMs), RAG architectures, and agent-based frameworks while collaborating closely with engineering teams to drive AI adoption and innovation.
Experience
6-12 years
Location
Mumbai / Bangalore
Mode of Work
Hybrid
Mandatory Skills (Must Have)
• Python programming (6+ years) including asynchronous programming and backend application development
• Java and Spring Framework (3+ years) for enterprise-scale application integration
• Azure OpenAI Service, Azure AI Foundry, and Azure AI Search for production GenAI applications
• Retrieval Augmented Generation (RAG) architecture including embeddings, chunking, vector databases, reranking, and grounding techniques
• Agent Frameworks such as Microsoft Agent Framework, Semantic Kernel, AutoGen, LangChain, or LangGraph
• Snowflake and Cortex AI (Cortex Search, LLM Functions) with strong SQL expertise
• Prompt Engineering, LLM evaluation frameworks, testing, and model performance optimization
• DevOps and Cloud Deployment using Azure DevOps, GitHub Actions, Docker, AKS, Azure Functions, and observability tools
Optional Skills (Good to Have)
• React.js for AI-powered user interfaces and conversational applications
• Azure AI Content Safety and Responsible AI implementation experience
• Financial Services, Banking, or other regulated industry domain experience
• Real-time streaming applications and token-level LLM operations
• Performance optimization, caching strategies, and cost optimization for AI workloads
• Microsoft Azure AI Engineer Associate Certification
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.
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)
PRINCIPAL AI ENGINEER @ METADOME.AI
Company Description
Metadome.ai builds frontier AI models that transform text, drawings, and CAD into production-ready, interactive 3D experiences. The company advances a full generative pipeline—text-to-CAD, 2D-to-3D
reconstruction, CAD completion and harmonization, and real-time interactive rendering—engineered for the precision required in the physical world. Its technology currently powers the modernization of
OEM aftersales for more than 30 automotive and heavy-equipment manufacturers worldwide, delivering accurate, scalable, and fast 3D solutions. Metadome.ai’s platform enables shoppable 3D parts, step-by-step repair animations, and a headless API that feeds consistent 3D assets into commerce, dealer, training, and service systems. The broader mission is to allow anyone to move from an idea, drawing, or specification to a production-grade 3D model and beyond in seconds.
Role Description
As a Principal AI Engineer — Generative CAD & 3D, you will lead the design, development, and deployment of advanced AI models that convert text, 2D drawings, and CAD files into engineering-grade 3D content. You will architect end-to-end generative pipelines, including
text-to-CAD, 2D-to-3D reconstruction, CAD completion, and real-time rendering, collaborating closely with product, design, and engineering teams to ship robust production systems. Day-to-day, you will experiment with novel neural network architectures, optimize model performance on large-scale CAD datasets, write high-quality production code, and guide the integration of AI services into customer-facing platforms. You will mentor other engineers, establish best practices for AI development, and contribute to technical strategy and roadmap. This is a full-time, hybrid role based in Bengaluru, with a mix of on-site collaboration and work-from-home flexibility.
Qualifications
- Strong foundation in Computer Science and Software Development, including data structures, algorithms, system design, and production-grade coding in languages such as Python, C++, or similar.
- Deep expertise in Neural Networks and Pattern Recognition, with hands-on experience designing, training, and deploying modern deep learning architectures for complex, high-dimensional data.
- Experience with Natural Language Processing (NLP), including working with text encoders, multimodal models, and integrating language understanding into generative workflows.
- Advanced degree (Master’s or PhD) in Computer Science, Electrical Engineering, Applied Mathematics, or a related field, or equivalent practical experience in AI/ML research and engineering.
- Background in 3D geometry, CAD, computer graphics, or related domains, with familiarity in 3D representations, mesh processing, and rendering pipelines.
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
🚀 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 – 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.
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.
About the Role We are seeking a highly technical, hands-on Senior AI/ML Tech Lead to drive the design, development, and deployment of cutting-edge Generative AI applications. In this dual-impact role, you wi l act as a primary individual contributor architecting core AI engines while simultaneously leading a team of engineers through task alocation, code reviews, and technical mentorship. The ideal candidate bridges the gap between state-of-the-art AI research (LLMs, Agentic frameworks, Advanced RAG, OCR) and production-grade ful-stack engineering (Python, FastAPI, React).
Key Responsibilities
Technical Leadership & Team Management (40%)
● Technical Oversight: Lead a team of AI, backend, and ful-stack engineers; alocate tasks, establish sprint priorities, and ensure timely delivery.
● Code Quality & Reviews: Conduct rigorous code reviews to maintain high engineering standards, security, performance, and scalability across AI and fu l-stack codebases.
● Architecture & Governance: Design end-to-end system architectures for AI solutions, ensuring seamless integration between frontend interfaces, backend APIs, and AI models.
● Mentorship: Guide and upskil team members on modern software practices, LLM engineering, and agentic design patterns. Hands-On Engineering & Development (60%)
● Generative AI & Agentic Systems: Architect, build, and optimize LLM-powered applications, multi-agent workflows (e.g., CrewAI, AutoGen, LangGraph), and autonomous AI agents.
● RAG & OCR Pipelines: Design and deploy advanced RAG (Retrieval-Augmented Generation) architectures and document processing pipelines utilizing OCR techniques (e.g., LayoutLM, PaddleOCR, Tesseract, Vision LLMs) to extract structured data from unstructured sources.
● Backend Systems: Build robust, asynchronous, high-throughput microservices and RESTful APIs using Python and FastAPI.
● Frontend Integration: Colaborate on or build modern web interfaces using React (e.g., Control Towers, operations dashboards, interactive chat interfaces).
● MLOps & Vector DBs: Oversee model deployment, prompt engineering, fine-tuning, vector database integration (Pinecone, Qdrant, Chroma, PGVector), and cloud infrastructure setup (Azure/AWS).
Required Qualifications & Skills
● Overall Experience: 8 to 10 years of professional software engineering experience.
● AI/ML Domain Experience: 3 to 4+ years of dedicated, hands-on experience building and deploying AI/ML, OCR, and Generative AI solutions in production.
● Core Technical Stack: ○ Generative AI & LLMs: Extensive experience with commercial and open-source LLMs (OpenAI, Anthropic Claude, Llama), Agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI), and LLM evaluation frameworks (LangSmith, TruLens, Ragas). ○ RAG & Unstructured Data: Strong knowledge of hybrid search, re-ranking, chunking strategies, vector databases, and document inte ligence workflows. ○ OCR & Vision Techniques: Hands-on experience with OCR engines (Tesseract, PaddleOCR, Azure Document Inteligence) and Multi-Modal/Vision LLMs for document extraction. ○ Backend: Deep expertise in Python and asynchronous frameworks (FastAPI, AsyncIO). ○ Frontend: Working proficiency in React (TypeScript/JavaScript) for building interactive web UI components. ○ Cloud & DevOps: Hands-on experience with cloud platforms (Azure / AWS), Docker, Kubernetes, and CI/CD pipelines.
Preferred / Good-to-Have Skills
● Experience with cloud-native data platforms (e.g., Microsoft Fabric, Snowflake, Azure SQL).
● Familiarity with cost optimization and latency reduction techniques for LLM inference (caching, semantic routing, model quantization).
● Prior experience in client-facing technical leadership or agile consulting environments.
What We Offer
● Opportunity to lead and build high-impact, state-of-the-art Generative AI systems.
● Colaborative engineering culture with room for technical ownership and direct business impact.
● Flexible work arrangements and competitive compensation package.
Job Description:
We are looking for a hands-on AI Engineer with experience in Generative AI and Agentic AI to build and deploy production-ready AI solutions.
Key Responsibilities:
- Develop and deploy GenAI and Agentic AI applications.
- Build RAG pipelines, LLM workflows, and AI agents.
- Develop solutions using Python, LangChain, LangGraph, LlamaIndex, or similar frameworks.
- Implement tool calling, context retrieval, and LLM orchestration.
- Integrate AI solutions with APIs and cloud platforms.
- Work with AWS/Azure/GCP, Docker, and CI/CD.
Required Skills:
- Strong Python programming skills.
- 3+ years of GenAI/Agentic AI experience.
- RAG and LLM orchestration.
- LangChain / LangGraph / LlamaIndex / AutoGen / CrewAI / Semantic Kernel.
- MCP and A2A knowledge.
- Cloud, APIs, Docker, and CI/CD experience.
Preferred Experience:
Hands-on experience building and deploying production-ready AI solutions.











