AI Strategy Consultant

E2M; Ahmedabad District; In loco; INR 1.500.000 - 3.000.000; Tempo pieno

Descrizione del lavoro

E2M seeks an experienced AI Engagement Lead to own client AI initiatives end-to-end, from discovery through deployment and adoption. You will drive structured assessments, craft blueprints, and guide a delivery pod, ensuring secure, scalable, production-ready solutions.

You will collaborate with agency partners, manage outcomes, and mentor junior teammates while aligning with business goals and budgets.

Competenze

• 2+ years building production AI solutions (LLM apps, RAG, agents).
• 4+ years in client-facing delivery roles like PM/CSM/consulting.
• Experience owning multiple concurrent client engagements end-to-end.

Mansioni

• Own AI engagements from discovery to live, adopted solutions.
• Run AI assessments with stakeholders across disciplines.
• Author AI blueprints with use cases, solutions, timelines.
• Lead platform decisions: hosting, build/buy, security, and cost.
• Mentor junior team members and manage client communications.

Conoscenze

AI solution design

Client delivery leadership

Cloud platforms

Security and RBAC

Strumenti

Python with FastAPI

LangGraph

MCP servers/connectors

APIs/webhooks

OAuth/SAML/SSO

Azure/AWS/GCP

Postgres/Supabase

Descrizione del lavoro

E2M is a leading white-label growth partner for digital agencies worldwide, helping them scale through expert web development, digital marketing, and AI-powered solutions.

With 13+ years of experience, 350+ professionals, and 400+ agency partners globally, E2M offers services across WordPress, Shopify, SEO, PPC, content marketing, and AI automation.

Driven by an agency-first approach and our Black Label Standard, we work as an extension of our partners' teams, delivering quality, innovation, and reliable digital solutions that help them grow.

Role Overview:

• You will own AI engagements for our agency clients, from the first discovery call to live, adopted solutions. Our clients know AI matters but are held back by manual work, inconsistent AI output, and disconnected tools.
• You will find where time and money are being lost, define what to build and in what order, make sound architecture and security calls, and lead an engineering pod to ship production-ready systems. You are the person clients trust when things go right, and just as importantly, when they go wrong.

Key Responsibilities:

1. Discovery and Assessment

• Run a structured 3 to 4 week AI assessment with stakeholders across PPC, SEO, content, project management, sales, and leadership.
• Use pre-call audit sheets to quantify manual work (task, frequency, hours) and steer toward the highest-value workflows.
• Map workflows end to end (tools, handoffs, data sources, failure points) and reframe solution-first requests into the real underlying problem.

2. AI Blueprint and Proposal

• Author the client AI Blueprint: 10 to 30+ use cases, each with current process, proposed solution and stack, dependencies, expected outcome, and timeline.
• Prioritise with an Impact vs. Effort matrix and recommend 2 to 3 high-impact starting automations.
• Design phased roadmaps (quick wins, leadership visibility, revenue and lead generation, then agentic systems) that build on existing tools.
• Present the plan to founders, covering team model, delivery cadence, testing approach (for example shadow mode), and pricing.
• Lead platform, hosting, and build vs. buy decisions with client technical teams (Azure AI Foundry, Claude, OpenAI, Gemini, multi-model).
• Define secure access: least privilege, read-only API scopes, SSO/SAML, RBAC, audit trails, and exclusion of sensitive data.
• Design knowledge systems: RAG pipelines, vector search trade-offs, tiered context management, MCP connectors, and reusable Claude Skills.
• Test feasibility on client APIs before scoping, manage cost-to-serve, and make deliberate "prototype now, re-architect later" calls.

4. Delivery and Account Management

• Run weekly syncs per account: demo progress, collect feedback, manage change requests, and reprioritise.
• Turn feedback into clear, testable requirements for the pod and hold the line on MVP dates.
• Own AI output quality: lead root cause analysis on failures, put safe interim processes in place, and track accuracy over time.
• Lead client communication on security incidents, covering impact, actions, and timelines.

5. Adoption and Training

• Train client teams through live sessions, SOPs, and follow-up coaching so solutions are used after launch.
• Ensure AI output matches each client’s brand voice and coach clients on giving feedback that improves it.
• Direct the delivery pod: set requirements, review builds, and enforce a production-ready definition of done, edge cases included.
• Mentor junior team members toward client-facing roles through frameworks, scenario reviews, and call shadowing.

Requirements:

1. Experience

• 2+ years building custom AI solutions (LLM apps, RAG, agents, workflow automation) that reached production.
• 4+ years in client-facing delivery (Project or Program Manager, Solutions Consultant, CSM, or Account Manager), ideally in an agency or services company.
• Track record of owning multiple concurrent client engagements end to end.

2. Technical Skills

• AI: Claude, OpenAI, Gemini, prompt and context engineering, RAG, embeddings, vector search, output evaluation.
• Build: Python with FastAPI or LangGraph, MCP servers and connectors.
• Integration: APIs, webhooks, OAuth scopes, SSO/SAML, RBAC, secure credential handling, plus one cloud (Azure, AWS, or GCP) and Supabase or Postgres.
• Agency stack: GA4, Search Console, Google, Meta and Bing Ads, Klaviyo, SEO data providers, HubSpot, and PM tools (Teamwork, Basecamp, ClickUp, Monday, Productive).
• Judgment: Can sketch an architecture, estimate effort, and spot feasibility risks without an engineer in the room.

3. Consulting Skills

• Facilitates discovery workshops that surface the real problem.
• Quantifies ROI (hours saved, turnaround time, cost avoided) and uses it to prioritise.
• Writes clear proposals, Blueprints, requirements, and SOPs.
• Presents confidently to executives and discusses pricing, phasing, and scope in plain business language.

Nice to Have

• Experience productising a custom AI solution across multiple clients.
• PMP, PRINCE2, or equivalent delivery certification.
• Consulting background with exposure to process improvement and quality frameworks.
• Experience with AI search visibility, SEO intelligence, or marketing analytics.