Position : Founding AI Forward Deployment Engineer / Architect

Overall/Total Experience : 7 - 10 years

Location : Hyderabad

Working Days : 5 Days from Office

Notice Period Requirement : 60 Days (Maximum)

Client's Company Size : Startup/Small Enterprise

- Mandatory Face to Face Interview at Hyderabad Office

Roles & Responsibilities :

- Lead the pre-sales and technical discovery sessions with enterprise and mid-market clients globally.

- Own the solution design for AI proposals : use case scoping, high-level system design, data requirements, and ROI framing.

- Build and present compelling PoC demos, solution blueprints, and technical proposals in partnership with the commercial team.

- Respond to RFPs and RFIs with technically rigorous and commercially sharp responses that win confidence.

- Act as a trusted AI advisor to client stakeholders - CXOs, VPs of Operations, IT leaders.

- Run workshops, AI readiness assessments, and value stream mapping sessions at client sites and remotely.

- Build long-term client relationships that translate into deepened engagements, referrals, and expanded mandates.

- Collaborate with engineering and data science teams to ensure solution designs are buildable and delivered to the quality clients expect.

- Drive go-live milestones, client acceptance, and post-deployment success metrics with accountability.

- Debug, iterate, and adapt.

- Define AI architecture patterns for the firm : LLM orchestration, RAG pipelines, agentic workflows, multi-modal systems.

- Develop the whole tech department.

Candidate Requirements :

- Must have 7+ years of experience, with hands-on production AI/ML work (LLMs, NLP, computer vision or advanced analytics).

- Must be deeply hands-on, able to build SLMs, agentic structures, RAG pipelines, LLM orchestration and multi-modal systems, and get into cost/credit optimisation detail, not just high-level oversight.

- Must have 4+ years client-facing as a trusted AI advisor to CXOs/VPs of Operations/IT leaders, with a proven presales/solution-consulting track record.

- Must have designed and deployed end-to-end AI systems (ingestion, pipelines, deployment, monitoring, iteration), owning production constraints, integration, change management, go-live, client acceptance and post-deployment success, owning outcomes.

- Must have built and led their own team, creating a pod structure per project, and mentored junior AI engineers and consultants.

- Must be hands-on with Python, LLM frameworks (LangChain/LlamaIndex/HuggingFace) and cloud AI (AWS/Azure/GCP).

- Must have strong pedigree, ideally IIT, then BITS/NITs/IIITs, with a CSE/IT background.