Pre-Sales AI Solution Architect (Enterprise AI Platforms)

Computer Enterprises/CEI INDIA; Chennai; Hybrid; INR 4,000,000 - 9,000,000; Full time

Job summary

Computer Enterprises/CEI INDIA seeks an experienced Pre-Sales AI Solution Architect (Chief Digital Officer level) to translate complex business problems into production‑grade AI solutions across GenAI, agentic workflows, and orchestration. You will design end‑to‑end architectures, lead workshops, build demos, and drive POCs.

Leverage Microsoft/Azure, AWS, Databricks ecosystems with governance, observability, and cost controls. Strong hands‑on coding in Python and LangChain is required.

Qualifications

• 10+ years in software/solution architecture, with strong focus on AI/ML/GenAI platforms.
• 4+ years in pre‑sales, solution architecture, or consulting roles focused on AI/GenAI/ML.
• 2+ years hands‑on building agentic or workflow platforms (orchestration, governance, evaluation, observability).
• Proven experience delivering technical pre‑sales activities: discovery workshops, architecture presentations, POCs, and proposal writing.
• Deep understanding of enterprise constraints: security, compliance, identity, data governance, cost control.
• Strong communication and storytelling skills to speak business and technical languages.
• Hands‑on coding proficiency (Python, LangChain/LlamaIndex, Azure/AWS AI services).

Responsibilities

• Lead technical discussions with customers to deeply understand objectives, processes, data landscape, and constraints.
• Map customer needs to AI/GenAI capabilities: agents, multi-agent workflows, RAG, governance, etc.
• Design end‑to‑end solution architectures combining custom development, vendor services, and platform offerings.
• Create high‑quality solution diagrams, architecture documents, effort estimates, and ROI/business cases.
• Build rapid prototypes, interactive demos, and proofs‑of‑concepts in customer environments to validate fit.
• Own architecture and implementation of reference components during pre‑sales cycles.
• Support platform elements for agent registries, workflow orchestration, tooling layer, observability, and governance guardrails.
• Architect production‑ready agentic systems with multi‑step reasoning, human‑in‑the‑loop, deterministic workflows, and safe execution.
• Guide customers on patterns like workflows as agents and agents executing workflows while preventing ad‑hoc implementations.
• Advise on stability as vendor models and services evolve.
• Position governance layers including RBAC/ABAC, audits, reliability KPIs, and cost governance.
• Help customers meet security, compliance, data privacy, and auditability requirements.
• Design pluggable architectures integrating Microsoft/Azure AI, AWS Bedrock/SageMaker, Databricks, and others.
• Contribute to or lead technical sections of proposals, RFPs, and SOWs; participate in executive presentations and negotiations.
• Productize successful solutions into reusable assets and share best practices via webinars and workshops.

Skills

AI/GenAI platforms

Pre-sales experience

Agentic/workflow platforms

Solution architecture

Python

LangChain

Azure AI

AWS AI services

Tools

Azure

Bedrock/SageMaker

Databricks

Job description

CHIEF DIGITAL OFFICER

Reporting to: Head of Pre-Sales / CPO (dotted line to Sales Leadership) Role Overview We are hiring an experienced Pre-Sales AI Solution Architect to work with enterprise customers on identifying, scoping, and architecting GenAI, Agentic AI, and AI platform opportunities. You will translate complex business problems into high-value AI solutions built on vendor-agnostic enterprise AI platforms (agents, workflows, orchestration, governance, and observability).

This is a customer-facing, hands‑on technical pre-sales role. You will engage directly with prospects and customers, understand their business needs and pain points, design solution architectures, lead technical workshops, build prototypes/demos, support POCs, and craft winning proposals/RFPs. You must have deep prior experience building (not just designing) production‑grade agentic and workflow platforms so you can credibly advise customers and avoid common pitfalls.

Core Requirement:

You have previously architected and built (hands‑on) an agent/workflow platform or framework with real production controls (governance, evaluation, observability, cost management). This experience is essential for credible pre‑sales conversations at the enterprise level.

The solutions you design will leverage major vendor ecosystems (Microsoft/Azure, AWS, Databricks, Google, etc.) via clean abstractions, enabling rapid adoption without lock‑in.

Key Responsibilities:

1) Customer Discovery & Solution Architecture:

• Lead technical discussions with customers to deeply understand business objectives, processes, data landscape, and constraints.
• Map customer needs to AI/GenAI capabilities: agents, multi-agent workflows, RAG, evaluation frameworks, governance, etc.
• Design end‑to‑end solution architectures that combine custom development, vendor services, and our platform offerings.
• Create high‑quality solution diagrams, architecture documents, effort estimates, and ROI/business cases.

2) Hands‑On Prototyping, Demos & POCs:

• Build rapid prototypes, interactive demos, and proof‑of‑concepts (often in customer environments) to validate solution fit.
• Own both architecture and implementation of reference components during pre‑sales cycles.
• Support the build of platform elements that support:
• Agent registries (roles, permissions, tool access, escalation rules)
• Workflow orchestration (state, retries, branching, approvals, audit trails)
• Tooling layer & evaluation/QA harnesses
• Observability, cost telemetry, and governance guardrails

3) Agentic Workflows + Orchestration (Production‑Grade Advice):

• Architect production‑ready agentic systems with multi‑step reasoning, human‑in‑the‑loop, deterministic workflows, and safe execution.
• Guide customers on patterns such as workflows as agents and agents executing workflows while preventing ad‑hoc implementations.
• Advise on stability as underlying vendor models and services evolve.

4) Governance, Controls, Security & KPI Framework:

• Position and design first‑class governance layers including:
• Policy/Guardrails (RBAC/ABAC, allow/denylists, approvals, audit)
• Reliability & Quality KPIs (success rate, containment, precision/recall, drift detection)
• Cost/latency governance and observability
• Help customers meet enterprise requirements around security, compliance, data privacy, and auditability.

5) Vendor‑Agnostic Platform Strategy:

• Design pluggable architectures that integrate Microsoft (Azure AI, Fabric), AWS (Bedrock, SageMaker), Databricks, and other providers.
• Recommend optimal make‑vs‑buy and core‑vs‑plugin decisions based on customer context.

6) Proposal, RFP & Deal Support:

• Contribute to or lead technical
• sections of proposals, RFPs, and SOWs.
• Participate in sales meetings, executive presentations, and negotiations on technical feasibility and differentiation.
• Work closely with Account Executives and Delivery teams for seamless handoff to implementation.

7) Productization & Knowledge Sharing:

• Convert successful customer solutions into reusable assets (templates, accelerators, reference architectures).
• Share best practices internally and with customers through webinars, whitepapers, and workshops.

Required Qualifications (Hard Requirements)

• 10+ years in software/solution architecture, with strong focus on AI/ML/GenAI platforms.
• 4+ years in pre‑sales, solution architecture, or consulting roles focused on AI/GenAI/ML (critical).
• 2+ years hands‑on building agentic or workflow platforms (orchestration, governance, evaluation, observability) using Microsoft, AWS, Databricks, or similar ecosystems.
• Proven experience delivering technical pre‑sales activities: discovery workshops, architecture presentations, POCs, and proposal writing.
• Deep understanding of enterprise constraints: security, compliance, identity, data governance, cost control.
• Strong communication and storytelling skills ability to speak both business and deep technical languages.
• Hands‑on coding proficiency (Python, LangChain/LlamaIndex, Azure/AWS AI services, etc.).

What Success Looks Like (First 90–180 Days)

• Successfully support multiple qualified opportunities from discovery to closed‑won.
• Deliver high‑impact technical workshops and compelling solution architectures that advance deals.
• Build and maintain a library of reusable demos, accelerators, and reference architectures.
• First 2–3 customer POCs or pilot workflows go live with proper governance, evaluation, observability, and KPIs.
• Positive feedback from sales teams and customers on technical credibility and solution quality.