AI Solutions Architect / FDE

D2R AI Labs; Chennai District; Hybrid; INR 3,000,000 - 5,000,000; Full time

Job summary

D2R AI Labs seeks a hands-on Senior AI Solutions Architect / Forward Deployed Engineer with 8-12 years of experience to design, deploy and scale enterprise AI solutions. You will own delivery from discovery to production, bridging customer requirements with engineering and product teams.

Role involves direct enterprise engagement, architecture workshops and building production-grade AI applications using Python and modern AI/ML frameworks with containerized deployment on cloud platforms.

Qualifications

• 8-12 years of software/technology experience with AI/ML and enterprise architecture.
• Proven ability to independently lead discovery sessions with senior business stakeholders.
• Production experience delivering Generative AI, RAG, LLMs/SLMs, embeddings or AI agent architectures.

Responsibilities

• Design scalable, production-ready AI/ML architectures and solutions.
• Own delivery from discovery and POC through production deployment and optimization.
• Lead architecture workshops, technical discussions and customer presentations.

Skills

AI architecture

Customer-facing delivery

Python

LangChain/LangGraph

System design

ML frameworks

Cloud platforms

Docker/Kubernetes

ERP/CRM integration

GPU infrastructure

Tools

Docker

Kubernetes

REST APIs

Databases (SQL/NoSQL)

Job description

D2R AI Labs is looking for a hands-on Senior AI Solutions Architect / Forward Deployed Engineer (FDE) with 8-12 years of experience to design, build, deploy and scale enterprise AI solutions.

Most GenAI projects don't fail at the model. They fail in the gap between a demo and a client's production environment. This role exists to close that gap - combining AI engineering, solution architecture, enterprise integration and direct customer ownership, from business discovery and architecture through production deployment and optimisation.

This is customer-facing ownership, not internal development or architecture documentation alone.

Full job description: https://docs.google.com/document/d/18KoIX0NCNOw3spiMtwalcU25hDnV7Ikj/preview

DETAILS

• Experience: 8-12 years
• Compensation: INR 30-50 LPA, based on experience, technical depth, certifications and customer-facing capability
• Location: Flexible - Remote, Hybrid or in-office (Chennai), based on what works for you
• Engagement: Full-time, Contract or C2H

WHAT YOU'LL DO

AI architecture and solution design

• Design scalable, secure, production-ready AI/ML and Generative AI architectures.
• Architect solutions using LLMs/SLMs, RAG, Agentic AI, AI agents, embeddings, vector databases and retrieval systems.
• Translate business requirements into technical architectures, technology choices and implementation roadmaps.
• Balance performance, latency, scalability, security and cost when selecting models and architectures.

Customer-facing / FDE ownership

• Work directly with enterprise customers and senior stakeholders to identify high-value AI opportunities.
• Own delivery from discovery and POC through production deployment, adoption and optimisation.
• Lead architecture workshops, technical discussions, solution demos and customer presentations.
• Bridge customer requirements with engineering and product teams, and rapidly validate solutions in real-world environments.
• Build production-grade AI applications using Python and modern AI/ML frameworks.
• Develop RAG pipelines covering ingestion, chunking, embeddings, indexing, retrieval, reranking, context management and evaluation.
• Build and orchestrate AI agents and workflows using LangChain, LangGraph or equivalent frameworks.
• Work with LLM/SLM APIs, open-source models, fine-tuning, inference optimisation and model evaluation.
• Develop APIs, backend services and scalable data pipelines for enterprise AI applications.

Enterprise deployment and integration

• Integrate AI solutions with ERP, CRM, ITSM/ticketing systems, databases, business applications and third-party APIs.
• Deploy using Docker, Kubernetes and major cloud platforms (AWS, Azure or GCP).
• Work with GPU infrastructure, model serving, inference optimisation, scalability, latency and cost optimisation.
• Implement AI observability, monitoring, evaluation and production performance measurement.

Technical leadership

• Drive architecture decisions, engineering standards, reusable patterns and AI development frameworks.
• Mentor engineers and provide technical direction across AI and software engineering initiatives.
• Create reusable AI playbooks, accelerators, frameworks and best practices.

WHAT YOU'LL BRING (MUST-HAVE)

• 8-12 years of overall software/technology experience, with significant AI/ML and/or enterprise architecture experience.
• Strong customer-facing technical delivery and enterprise stakeholder management - proven ability to independently lead discovery sessions and technical conversations with senior business stakeholders.
• Production experience with Generative AI, RAG, LLMs/SLMs, embeddings, retrieval systems and/or Agentic AI.
• LangChain and/or LangGraph experience.
• Strong software architecture and AI system design capabilities.
• Experience taking AI solutions from POC/prototype to production.
• Experience integrating with at least one major enterprise system: ERP, CRM, ITSM/ticketing, database or business API.

NICE TO HAVE

• Palantir Foundry certification (Application Developer / Data Engineer track - AIP, Ontology) and hands-on Foundry/AIP experience.
• GPU optimisation and large-scale model inference.
• AI evaluation frameworks and production observability.
• Fine-tuning and preference optimisation (LoRA, QLoRA, PEFT, distillation, DPO, GRPO).
• Experience building reusable AI platforms, accelerators or internal frameworks.
• Domain experience in Banking & Finance (preferred) or Energy & Utilities.
• Strong executive-level communication and presentation skills.

THE IDEAL CANDIDATE

Someone who can walk into a customer environment, understand the business problem, design the AI solution, build and integrate it, take it to production, and keep improving its performance and business impact.

• Clear, end-to-end ownership: business problem to architecture to prototype to production.
• Strong coding ability alongside architecture and system-design skills.
• The ability to make, explain and defend technical architecture decisions.
• Proven stakeholder management - comfortable independently driving discovery sessions with senior business stakeholders, not just engineering teams.
• A track record of operating AI systems in production with measurable business impact.