Gen AI Architect

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Role Overview

Senior GenAI Consultant / Architect

deep hands-on GenAI expertise

Key Responsibilities

GenAI Architecture & Solution Design

• Design

  end-to-end Generative AI solutions

  aligned with enterprise architecture standards.
• Define

  scalable, secure, and cost-efficient GenAI architectures

  across cloud and hybrid environments.
• Own technical solution design from

  POC to production

  , ensuring reliability, performance, and governance.
• Identify and evaluate appropriate GenAI patterns such as

  RAG, fine-tuning, prompt orchestration, and agent-based systems

  .

LLM & Advanced AI Expertise

• Work extensively with

  Large Language Models (LLMs)

  including:
• OpenAI / Azure OpenAI
• Anthropic
• Open-source LLMs (Llama, Mistral, etc.)
• Apply advanced

  prompt engineering

  ,

  model fine-tuning

  ,

  embeddings

  , and

  retrieval-augmented generation (RAG)

  techniques.
• Design and optimize inference pipelines for latency, cost, and quality.

Data & ML Foundations

• Design AI solutions involving:

• Regression models

  , forecasting, and

  time-series analysis

• Model selection, evaluation, and validation
• Architect data ingestion pipelines handling

  structured and unstructured data

  .
• Work with

  vector databases

  ,

  feature stores

  , and embeddings for GenAI workflows.
• Ensure data quality, lineage, and governance for AI-driven systems.

Cloud & Platform Engineering

• Architect and deploy GenAI solutions on

  AWS, Azure, and GCP

  , leveraging native GenAI services.
• Design

  API-based architectures

  and microservices for AI consumption.
• Use

  containerization (Docker/Kubernetes)

  for scalable and portable deployments.
• Ensure integration with enterprise systems, security, and monitoring frameworks.

Client Advisory & Consulting

• Lead

  client advisory engagements

  , including requirement discovery and solution workshops.
• Translate complex

  business problems into practical AI-driven solutions

  .
• Communicate architecture decisions, trade-offs, and value propositions to both technical and non-technical stakeholders.
• Support pre-sales activities including solution proposals, estimations, and technical presentations.

Technical Leadership & Mentoring

• Provide

  technical mentoring

  to engineers and junior architects.
• Establish best practices, coding standards, and architectural guidelines.
• Collaborate with cross-functional teams including product, data, platform, and security teams.
• Act as a

  technical owner

  for GenAI initiatives across multiple workstreams.

Mandatory Skills & Experience

• 10–15 years

  of overall experience in software engineering, data science, or AI/ML roles.
• Proven experience designing

  enterprise-grade GenAI architectures

  .
• Deep hands-on expertise with

  LLMs, prompt engineering, fine-tuning, RAG, and embeddings

  .
• Strong background in

  regression modeling, forecasting, and time-series analysis

  .
• Experience with

  data ingestion pipelines

  , vector databases, feature stores, and unstructured data.
• Hands-on experience with

  AWS / Azure / GCP GenAI services

  .
• Strong understanding of

  API-driven architectures and containerized deployments

  .
• Demonstrated

  client advisory and stakeholder management

  experience.
• Ability to translate business requirements into scalable AI solutions.
• Experience in

  technical mentoring and solution ownership

  .

Preferred / Good to Have

• Experience deploying GenAI solutions in

  regulated or enterprise environments

  .
• Knowledge of AI governance, responsible AI, and model risk management.
• Exposure to MLOps / LLMOps practices.
• Experience with evaluation frameworks and GenAI observability tools.
• Prior consulting or advisory background.