AI Solutions Architect

Role: AI Solution Architect

Loc: 5 days office Hyderabad

Exp: 12+ years

Employment Type: Full Time

Job Summary

We are seeking a highly experienced
AI Architect / GenAI & Agentic Systems Lead
to design, develop, and scale enterprise-grade AI platforms and agentic solutions.

The ideal candidate will possess deep expertise across
Generative AI, AgentOps, cloud-native engineering, and AI platform strategy
, with hands-on proficiency in
LLMs, orchestration frameworks, and multi-cloud deployments
.

This role requires a strong technical leader who can architect and operationalize AI ecosystems aligned with enterprise governance, scalability, and compliance standards.

Key Responsibilities

• Design and implement
  end-to-end AI architectures
  — spanning data ingestion, experimentation, model deployment, observability, and lifecycle management.
• Lead the development of
  Agentic AI systems
  with advanced features such as AgentOps, observability, shared memory, A2A communication, and context-sharing via MCP.
• Architect and operationalize
  enterprise AI marketplaces/registries
  for governed, self-service publishing and consumption of models, datasets, and agents.
• Build and manage
  horizontal AI services at scale
  — prompt/RAG APIs, vector & feature stores, guardrails, evaluation, and observability frameworks.
• Collaborate with data, cloud, and engineering teams to deliver
  multi-cloud AI platforms
  using AWS, Azure, and GCP (especially Vertex AI, Agentspace, ADK).
• Implement
  MLOps, AIOps, and DevSecOps
  best practices for AI and agent lifecycle deployment, security, and monitoring.
• Develop
  AI blueprints
  covering retrieval pipelines, tool use, safety, zero-trust access, and multi-tenant isolation.
• Drive
  transition from traditional AI → GenAI → Agentic architectures
  , supporting LLM fine-tuning, RAG workflows, and autonomous agents.
• Define and enforce
  AI governance, ethical AI, and data compliance
  frameworks aligned with enterprise policies.
• Lead cross-functional teams, ensuring
  SDLC and Agile
  process alignment, while mentoring engineers and data scientists.
• Partner with leadership to shape
  AI platform strategy, integration roadmaps
  , and enterprise-wide adoption frameworks.

Required Skills & Abilities

Programming & AI Frameworks

• Proficiency in
  Python
  ,
  Java
  ,
  C#
  , or
  R
  .
• Hands-on experience with
  Generative AI frameworks
  :
  TensorFlow, PyTorch, LangChain, OpenAI Codex, Claude, Gemini, HuggingFace
  .
• Strong understanding of
  ML/DL paradigms
  — supervised, unsupervised, and reinforcement learning.

Agentic AI & Autonomous Systems

• Experience with
  AgentOps
  ,
  Agent Observability
  , and
  Agent Lifecycle Management
  .
• Knowledge of
  MCP (Model Context Protocol)
  for context sharing and
  A2A (Agent-to-Agent)
  communication.
• Familiarity with
  Shared Memory architectures
  and
  Agentic Workflow Orchestration
  .
• Ability to design and evaluate
  deterministic vs autonomous
  agentic architectures.

Cloud & Platform Engineering

• Deep proficiency in
  AWS, Azure, and GCP
  (especially
  Vertex AI, Agentspace, and ADK
  ).
• Expertise in
  Infrastructure as Code (IaC)
  using
  Terraform, GitOps, Kubernetes
  .
• Strong grounding in
  SRE practices
  , including
  SLOs
  and
  error budgets
  .
• Experience integrating
  AI observability and policy enforcement gateways
  .

MLOps, AIOps & DevSecOps

• Practical experience implementing
  CI/CD pipelines
  ,
  model monitoring
  ,
  governance
  , and
  versioning
  .
• Skilled in
  AIOps for automated performance monitoring
  and
  DevSecOps
  for secure AI lifecycle management.

AI Architecture & Enterprise Integration

• Proven experience architecting
  AI Platforms
  ,
  registries
  , and
  shared services
  with lifecycle metadata and chargeback models.
• Strong understanding of
  data mesh
  ,
  policy-driven AI gateways
  , and
  multi-region resiliency
  .
• Knowledge of
  safety pipelines
  ,
  evaluation harnesses
  , and
  guardrail frameworks
  for LLMs and agents.

Ethical & Responsible AI

• Deep understanding of
  data governance
  ,
  privacy
  , and
  ethical AI principles
  .
• Experience implementing
  responsible AI frameworks
  ensuring transparency and compliance.

Leadership & Collaboration

• Strong
  leadership
  ,
  mentoring
  , and
  stakeholder engagement
  abilities.
• Excellent
  communication
  skills with cross-functional and executive teams.
• Proven ability to work in
  agile environments
  aligned with
  SDLC
  standards.