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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.

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