GenAI/Cloud - Architect

Envision Technology Solutions

India

Remote

INR 3,500,000 - 6,500,000

Full time

4 days ago
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Job summary

Envision Technology Solutions is seeking a Senior Manager - Generative AI Engineering to drive AI-led product innovation and engineering execution across enterprise programs. You will translate AI strategy into actionable plans, lead cross-functional teams of engineers, and deliver GenAI-based solutions, PoCs, and accelerators with a strong product mindset.

The role demands hands-on leadership in AI/ML frameworks, full‑stack development, and cloud-native architectures (preferably AWS), guiding a

Qualifications

  • Experience in AI/ML solution delivery (3–5 years).
  • Experience with MACH architecture and full‑stack development.
  • Proficiency in Python, Node.js, Java and frontend frameworks.
  • CI/CD, DevOps/MLOps pipelines and containerization (Docker/Kubernetes).
  • Experience with AWS AI services (SageMaker, Bedrock) and cloud deployments.

Responsibilities

  • Lead design and implementation of GenAI-driven solutions, PoCs, and client prototypes aligned with the GenAI roadmap.
  • Translate AI strategy into execution plans, manage timelines, risks and dependencies.
  • Collaborate to build AI accelerators, reusable components, and automation frameworks.
  • Drive integration of Generative AI into existing systems, including intelligent assistants and document automation.
  • Oversee architecture discussions, code quality, and AI governance adherence.

Skills

GenAI development
LLM design & deployment
Python
Full-stack development
MACH architecture
DevOps / MLOps
AWS knowledge

Tools

LangChain
LlamaIndex
Hugging Face
OpenAI APIs
PyTorch
TensorFlow
Docker
Kubernetes
SageMaker

Job description

The Senior Manager - Generative AI (GenAI) Engineering will play a pivotal role in driving the organization s AI-led product innovation and engineering execution.

Reporting to the Director / Senior Director - GenAI Engineering, this leader will be responsible for translating AI strategy into action, managing cross-functional engineering teams, and delivering GenAI-based solutions, frameworks, and proof-of-concepts (PoCs) across enterprise programs.

This role demands a hands-on engineering leader with strong expertise in AI/ML frameworks, full-stack product development, and cloud-native architectures (preferably AWS). The Senior Manager will guide a team of engineers, architects, and data practitioners, ensuring technical excellence, innovation, and delivery rigor.

The ideal candidate brings a product mindset, a passion for Experimentation AI-led transformation, and the ability to balance strategic thinking with deep technical execution.

1. AI Solution Delivery and Product Engineering
  • Lead the design and implementation of 1-2 GenAI-driven solutions, PoCs, and client-facing prototypes aligned with the enterprise GenAI roadmap.
  • Translate strategic AI initiatives into execution plans, managing delivery timelines, technical risks, and dependencies.
  • Collaborate with the Director and teams to build AI accelerators, reusable components, and automation frameworks for internal and client use cases.
  • Drive the integration of Generative AI capabilities into existing systems and applications - including intelligent assistants, document automation, and code intelligence.
  • Drive engineering quality, code reviews, and technical standards for AI solution delivery.
  • Contribute to architecture discussions, ensuring solutions are scalable, secure, and aligned with organizational standards.
2. Technical Leadership and Hands-on Contribution
  • Build GenAI solutions, LLM-based applications, and prompt engineering frameworks hands-on using Python, LangChain, Hugging Face, and related ecosystems.
  • Lead experimentation with fine-tuning, embedding strategies, and RAG architectures for enterprise use cases.
  • Act as the technical anchor within GenAI programs-able to guide teams and contribute directly when required.
  • Participate in architecture reviews and ensure adherence to AI governance principles.
  • Collaborate with data engineering and DevOps teams to ensure smooth AI/ML model deployment pipelines (MLOps / AIOps).
3. Talent Development and Team Leadership
  • Manage and mentor a team of AI engineers, full-stack developers, and architects.
  • Foster a learning culture, encouraging engineers to explore new GenAI tools, frameworks, and problem-solving methods.
  • Conduct regular code walkthroughs, design reviews, and innovation sessions to enhance team capability.
4. Collaboration and Stakeholder Management
  • Engage with clients and internal stakeholders to understand business problems and propose AI-driven solutions.
  • Collaborate with cloud, security, and infrastructure teams to ensure smooth deployment of AI applications.
  • Partner with leadership to present technical outcomes, PoC results, and capability showcases.
Technical Prowess
1. Generative AI and ML Expertise
  • Hands-on experience with AI development frameworks: LangChain, LlamaIndex, Hugging Face, OpenAI APIs, PyTorch, TensorFlow.
  • Experience in prompt engineering, RAG pipeline design, vector database integration, and LLM tuning.
  • Exposure to Agentic AI architectures, AI guardrails, and self-healing systems.
2. Product and Platform Engineering
  • Experience in software product engineering, with at least 3-5 years in AI/ML solution delivery.
  • Strong background in MACH Architecture, full-stack development, and cloud-native application design.
  • Proficiency in Python, Node.js, Java, or similar technologies for backend; and React, Angular, or Vue.js for frontend.
  • Experience in DevOps/MLOps/AIOps pipelines, CI/CD, and containerized environments (Docker, Kubernetes).
  • Proficiency in databases (SQL, NoSQL, graph, vector stores) and data modelling for AI use cases.
3. Cloud and Infrastructure Skills
  • Strong command of AWS ecosystem (SageMaker, Bedrock, ECS, Lambda, Redshift, IAM, KMS).
  • Experience deploying solutions on atleast one cloud ( AWS, Azure, or GCP) environments.
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