Generative AI Platform & Infrastructure Engineer

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. 

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.

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

• 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.

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’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 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.

Title - AI Integration Engineer

Experience: 2-5 years

Location: Hyderabad (Hybrid)

Role Summary:

We P99Soft are looking for an AI Integration Engineer who builds, deploys, runs, and optimizes agentic AI tools and pipelines. This role requires solid applied AI knowledge and some product understanding, but does not require building custom training pipelines or deep foundational research work - that responsibility sits with the AI Architect.

Key Responsibilities:

• Build, deploy, and run agentic AI tools and pipelines in production — retrieval-augmented generation systems, agentic bots, semantic search, and related tooling.
• Optimize existing AI tools for reliability, performance, and cost, working within an architecture defined by the AI Architect.
• Debug applied AI/systems issues as they arise in production, including model-serving failures and library/dependency or version compatibility problems.
• Collaborate with the AI Architect on implementation of system design decisions, and with product/GTM stakeholders on what's technically feasible to support adoption goals.
• Contribute to expanding tooling into adjacent areas as scope grows.

Required Experience & Skills:

• Applied, hands-on AI experience is non-negotiable — genuine experience building or integrating generative/agentic AI systems (LLMs, RAG, vision models), not just using AI assistants as an end user.
• Practical engineering skill in deploying and running AI systems in production — comfortable with the full build-deploy-optimize lifecycle for agentic tools.
• Some depth in AI systems internals — able to debug lower-level issues such as model serving cache failures or library/version compatibility problems, not just call existing APIs.
• Working understanding of generative/applied AI as distinct from traditional data science (regression, classification).
• Background can come from startup, founder, or self-taught paths — a traditional AI/data science pedigree is not required if applied AI fundamentals are genuinely strong.

Nice to Have:

• Some product understanding / awareness of how tools get adopted by end users, even though this is primarily an engineering role.
• Experience operating in a regulated, quality-driven, or highly technical enterprise environment.

Benefits:

• Competitive salary and performance-based bonuses.
• Comprehensive health insurance.
• Paid time off and flexible working hours.
• Professional development opportunities and support for continuing education.
• Udemy Learning Licenses to enhance skills and stay up-to-date with the latest technology.

P99Soft is an Equal-Opportunity Employer

P99soft is an equal-opportunity employer. At P99soft, we are committed to providing equal employment opportunities regardless of job history, disability, gender identity, religion, race, color, caste, marital/parental status, veteran status, or any other special status. We stand against the discrimination of employees and individuals and are proud to be an equitable workplace that welcomes individuals from all walks of life if they fit the designated roles and responsibilities.

Life @ P99Soft

At P99soft, we believe in creating a work environment that balances professional excellence with personal well-being. Our vibrant office culture is built on mutual respect, inclusivity, and a shared passion for innovation. We host regular team-building activities, workshops, and social events to foster a sense of community and collaboration among our employees. Join us and be part of a team that values your contributions and supports your growth.

About Us

P99soft is a leading IT Services and IT Consulting company dedicated to making our customers' business operations seamless by providing them with digital services and applications using the latest technologies. We are committed to bringing excellence to all our creations. We need passion, empathy, and being customer-focused to achieve technical excellence. We believe in transparency through open communication and work with honesty and integrity while dealing with our customers and partners.

Our Vision: “To lead digital transformation for our customers, delighting them at every step, while empowering our employees and fostering success.”

Our Mission: “To attain our objectives within a framework of integrity, transparency, and respect for our clients, employees, partners, and the community, fostering mutual trust and sustainable growth.”

Journey towards digital transformations begins here. Our talented teams help you make informed decisions, enhance operation efficiencies, create state-of-the-art visual interfaces, and design dynamic workflows to bring a better customer experience. Our engineering teams take complete ownership of assigning the right talent and architecting solutions using the latest technologies.

Title: AI Engineer - Product & Adoption Capability

Experience: 4-7 years

Location: Hyderabad

Mode of work: Hybrid

Role Summary:

P99Soft is hiring for an applied AI engineering role that also requires GTM-type capability - the ability to think about how AI tools actually get adopted by end users, not a dedicated go-to-market or marketing title. The engineer is expected to understand user workflows, spot adoption barriers, and shape how tooling gets rolled out, while remaining hands-on with applied AI work day to day.

Key Responsibilities:

• Build and support the rollout of AI-powered tools, driving awareness, onboarding, and adoption among target end users.
• Understand and map user workflows to identify where and why adoption of new AI tooling breaks down, and design solutions to close those gaps.
• Partner closely with engineering and architecture stakeholders to translate what's technically possible into what users will actually adopt and use.
• Gather and synthesize user feedback to inform product decisions and prioritization for the AI tooling roadmap.
• Apply hands-on applied AI knowledge to evaluate tool capability and limitations firsthand, rather than relying solely on engineering input.
• Communicate technical AI concepts to non-technical stakeholders in a way that drives buy-in and correct usage.

Required Experience & Skills:

• Applied, hands-on AI experience is non-negotiable - genuine exposure to building or working closely with generative/agentic AI systems, not just using AI assistants as an end user.
• Working GTM-type capability: comfort defining requirements, prioritizing based on user needs, and driving adoption of a tool - this can come from prior product exposure rather than a formal GTM title.
• Strong user empathy and the ability to identify practical adoption barriers for enterprise tools, distinct from purely technical blockers.
• Comfort operating with generative/applied AI systems (LLMs, agentic tools) as distinct from traditional data science approaches (regression, classification).
• Background can come from startup, founder, or self-taught paths — a traditional data science or enterprise pedigree is not required, provided applied AI fundamentals are genuinely strong.

Nice to Have:

• Some depth in AI systems internals (e.g., exposure to debugging model-serving or library/version compatibility issues) is a plus, though this role does not require building custom training pipelines from scratch.
• Experience operating in a regulated, quality-driven, or highly technical enterprise environment.

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive health insurance.
• Paid time off and flexible working hours.
• Professional development opportunities and support for continuing education.
• Udemy Learning Licenses to enhance skills and stay up-to-date with the latest technology.

P99Soft is an Equal-Opportunity Employer

P99soft is an equal-opportunity employer. At P99soft, we are committed to providing equal employment opportunities regardless of job history, disability, gender identity, religion, race, color, caste, marital/parental status, veteran status, or any other special status. We stand against the discrimination of employees and individuals and are proud to be an equitable workplace that welcomes individuals from all walks of life if they fit the designated roles and responsibilities.

Life @ P99Soft

At P99soft, we believe in creating a work environment that balances professional excellence with personal well-being. Our vibrant office culture is built on mutual respect, inclusivity, and a shared passion for innovation. We host regular team-building activities, workshops, and social events to foster a sense of community and collaboration among our employees. Join us and be part of a team that values your contributions and supports your growth.

About Us

P99soft is a leading IT Services and IT Consulting company dedicated to making our customers' business operations seamless by providing them with digital services and applications using the latest technologies. We are committed to bringing excellence to all our creations. We need passion, empathy, and being customer-focused to achieve technical excellence. We believe in transparency through open communication and work with honesty and integrity while dealing with our customers and partners.

Our Vision: “To lead digital transformation for our customers, delighting them at every step, while empowering our employees and fostering success.”

Our Mission: “To attain our objectives within a framework of integrity, transparency, and respect for our clients, employees, partners, and the community, fostering mutual trust and sustainable growth.”

Journey towards digital transformations begins here. Our talented teams help you make informed decisions, enhance operation efficiencies, create state-of-the-art visual interfaces, and design dynamic workflows to bring a better customer experience. Our engineering teams take complete ownership of assigning the right talent and architecting solutions using the latest technologies.