Gen ai Architect at aptask global · PAN india · 9 - 15 years · ₹20L - ₹70L / yr · Profitable · Posted 3 Aug 2026

Hi All,
Hope you are doing well,
If you are interested, please do revert back with the updated resume.
Position: Gen AI architect
Location: PAN India
Job Description:
AI/ML, Python, GenAI, Azure/AWS
Interview process:
1st level Assessment – HACKERRANK TEST(Candidate should be comfortable)

About aptask global
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Similar jobs (10)
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.
🚀 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
We’re on hunt for AI Architect
Responsibilities:
- 10–15+ years overall experience, with recent hands-on AI/GenAI architecture ownership.
- Must have architected enterprise AI platforms/solutions end-to-end, not just individual ML models or PoCs.
- Strong GenAI/LLM production experience: RAG, embeddings, vector DBs, hybrid search, reranking, evaluation, guardrails.
- Strong Agentic AI understanding: agents, tool calling, workflows, orchestration, human-in-the-loop.
- Experience taking AI solutions from architecture → production → scale, ideally across multiple business teams/use cases.
- Strong cloud architecture — Azure/AWS preferred; hybrid/on-prem experience is a plus.
- Must understand enterprise security, governance, Responsible AI, observability and LLMOps/MLOps.
- Should be able to articulate build-vs-buy, MVP-vs-target architecture, cost/performance/security tradeoffs.
- Strong stakeholder-facing / consulting ability — can work with business leaders, engineering, security and data teams and influence without authority.
There is scope to move to the US for this role if you are aligned for the same, else this will be a WFO role from Hyderabad location
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.
Hiring for AI Engineer
Exp: 6 - 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)
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
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
About the Role:
We are looking for an ideal candidate with 5+ years of experience in Data Science / Machine Learning, with strong hands-on experience in Generative AI, Large Language Models (LLMs), NLP, and AI-powered applications. The candidate should be comfortable working across the complete AI lifecycle—from understanding business requirements and experimenting with models to building, evaluating, deploying, and monitoring production-grade GenAI solutions.
The role requires a combination of strong technical expertise, business understanding, problem-solving ability, and stakeholder management skills.
Key Responsibilities:
Generative AI & LLM
· Design, develop, and deploy Generative AI and LLM-based solutions for enterprise use cases.
· Work with models such as OpenAI, Azure OpenAI, Llama, Mistral, Gemini, or equivalent LLM platforms.
· Develop applications using prompt engineering, structured outputs, function/tool calling, and LLM orchestration.
· Design and implement Retrieval-Augmented Generation (RAG) solutions.
· Work with vector databases and semantic search for enterprise knowledge retrieval.
· Develop and evaluate AI agents and multi-step AI workflows.
· Implement techniques such as prompt optimization, context management, grounding, and hallucination reduction.
· Develop AI solutions for text classification, summarization, information extraction, question answering, document intelligence, and other enterprise use cases.
Machine Learning & Data Science
· Develop and optimize traditional Machine Learning and statistical models where appropriate.
· Perform data exploration, feature engineering, model selection, training, validation, and evaluation.
· Apply appropriate ML and statistical techniques to solve business problems.
· Work with structured, unstructured, and semi-structured data.
· Develop scalable data pipelines to support AI/ML solutions.
· Collaborate with Data Engineers to prepare and manage data for AI applications.
AI Evaluation & Productionization
· Design evaluation frameworks to measure LLM accuracy, relevance, groundedness, toxicity, latency, and cost.
· Implement guardrails and responsible AI practices.
· Monitor model and application performance in production.
· Identify model/data drift and implement appropriate improvement strategies.
· Optimize AI solutions for performance, scalability, reliability, and cost.
· Support deployment and productionization of AI/ML solutions.
· Client & Delivery Responsibilities
· Work closely with the CEO, Delivery team, Solution Architects, Engineering teams, and clients to understand business problems and identify AI opportunities.
· Translate business requirements into practical AI/ML solutions.
· Participate in client discussions, solution presentations, technical workshops, and POCs.
· Develop rapid prototypes and demonstrate the feasibility of GenAI solutions.
· Convert successful POCs into scalable, production-ready applications.
· Provide technical guidance and contribute to AI solution architecture.
· Prepare technical documentation, solution approaches, and project estimates where required.
· Stay current with developments in Generative AI, LLMs, Agentic AI, and AI engineering.
Required Skills:
· 5+ years of hands-on experience in Data Science, Machine Learning, AI, or a related field.
· Strong practical experience in Generative AI and LLM-based applications.
· Strong proficiency in Python.
· Strong understanding of Machine Learning and statistical concepts.
· Hands-on experience with:
o LLMs
o Prompt Engineering
o RAG
o Vector Databases
o Embeddings
o Semantic Search
o LLM Evaluation
o AI Guardrails
· Experience with frameworks/tools such as LangChain, LangGraph, LlamaIndex, or equivalent.
· Experience with APIs and integrating LLMs into enterprise applications.
· Strong SQL and data handling skills.
· Experience working with large and complex datasets.
· Strong understanding of NLP concepts.XX
Technical Skills:
· Experience with OpenAI / Azure OpenAI / AWS Bedrock / Google Vertex AI.
· Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, or equivalent.
· Experience with Databricks, Snowflake, or cloud data platforms.
· Experience with Docker and CI/CD.
· Exposure to AWS, Azure, or GCP.
· Experience with ML/AI deployment and MLOps.
· Knowledge of AI security, data privacy, governance, and responsible AI.
· Experience building AI Agents / Agentic AI workflows.
· Experience with multimodal AI is an added advantage
Key Competencies
· Strong analytical and problem-solving ability.
· Ability to translate business problems into practical AI solutions.
· Strong communication and presentation skills.
· Ability to interact confidently with senior stakeholders and clients.
· Strong ownership and delivery mindset.
· Ability to work independently in a fast-paced environment.
- Strong experimentation and innovation mindset.
- Ability to balance technical feasibility, business value, scalability, and cost.
Required Education & Experience:
· Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related discipline
🚀 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 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
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.










