Key Skills PythonLLMComputer VisionAWSAzureGCPNLPLangChainLlamaIndexHuggingFaceRAGMLOpsSLMAgentic Workflows Roles & Responsibilities

- Lead the pre-sales and technical discovery sessions with enterprise and mid-market clients globally — understand their pain points, data maturity, and AI readiness before anyone writes a line of code

- 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 — not just a technical vendor on the call

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

- Navigate ambiguous problem spaces and help clients articulate what they actually want to solve with AI, and why it matters

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

- Be deeply involved in deployment — not just design. Understand production constraints, integration complexity, and change management realities

- 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: you own outcomes, not just deliverables. If something is broken, you fix it

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

- Stay ahead on applied AI research and emerging frameworks; bring relevant signals back to the team before the market does

- Mentor junior AI engineers and consultants on both client engagement craft and solution architecture rigour

- Contribute to Anthrobyte's knowledge capital — case studies, whitepapers, internal playbooks, and reusable solution accelerators

- Develop the whole tech department





- Create pods kind of a structure for each and every project Ideal Candidate 1Strong AI Forward Deployed Lead/Architect Profile owning the full journey from client discovery to production, hands-on and client-facing 2Mandatory (Experience 1): Must have 7+ years of experience, with hands-on production AI/ML work (LLMs, NLP, computer vision or advanced analytics) 3Mandatory (Experience 2): 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 4Mandatory (Experience 3): 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 (technical discovery, use-case scoping, solution design, ROI framing, PoC demos, blueprints, RFP/RFI responses) 5Mandatory (Experience 4): Must have run workshops, AI readiness assessments and value-stream-mapping sessions, navigated ambiguous problem spaces, and built long-term client relationships that lead to referrals and expanded mandates 6Mandatory (Experience 5): 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 and fixing what breaks 7Mandatory (Experience 6): Must have worked directly with enterprise-level clients in a client-facing capacity 8Mandatory (Experience 7): Must have built and led their own team, creating a pod structure per project, and mentored junior AI engineers and consultants 9Mandatory (Tech skill 1): Must be hands-on with Python, LLM frameworks (LangChain/LlamaIndex/HuggingFace) and cloud AI (AWS/Azure/GCP) 10Mandatory (Skill 1):



Must have strong storytelling, making complex AI accessible to business audiences without dumbing it down, and define AI architecture patterns and bring emerging frameworks/research back to the team 11Mandatory (Skill 2): Must take strong ownership, be genuinely enthusiastic and client-facing (not a pure-research or low-energy profile), thrive in ambiguity and 0 to 1 environments, and want to join long-term as part of the company (ESOP pool) 12Mandatory (Company): Must have experience across both services and product (this is a services-plus-product hybrid; candidates keen on pure product only are not a fit) 13Mandatory (Background): Must come from an AI/ML, data analytics or data-platform company with enterprise client delivery, ideally with startup or growing-company experience having seen AI build cycles in 0 to 1 / ambiguous environments; Supply Chain AI exposure, or manufacturing/logistics, B2B SaaS AI or MLOps background, a plus 14Mandatory (Pedigree): Must have strong pedigree, ideally IIT, then BITS/NITs/IIITs, with a CSE/IT background; robust equivalent capability also considered 15Mandatory (Note 1): CTC is inclusive of the variable component (around 25:75) 16Mandatory (Note 2): Must be open to starting on a consultant basis first, then converting to a full-time role 17Preferred (Global exposure): Global client exposure (US/Europe/Middle East/SEA) and cross-cultural fluency Additional Information

- This is a replacement role for a former AI Head/CTO
- The company is a one-year-old, self-funded, operationally positive startup of about 10 people

- Working model is a five-day week, 9 to 5 or 9 to 6

- The role reports to the CEO
- The company follows a hybrid model of services moving towards product (Services as a Software)

- Office location is Kokapate, Hyderabad Interview Process

- First call with Founder or CFO to discuss the role and background

- One or two technical rounds involving a live scenario to understand technical problem-solving know-how

- Mandatory face-to-face interview round at the Hyderabad office, create instagram banner without mention employer

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