About Nectar InnovationsNectar Innovations helps businesses turn AI opportunities into practical solutions that improve operations, enhance customer experiences, and drive measurable business outcomes.

We work with US businesses to identify opportunities for AI adoption, design AI-powered solutions, build intelligent applications, and automate business processes. Our capabilities span AI agents and agentic workflows, generative AI, conversational AI, business process automation, AI-native applications, CRM solutions, and digital transformation.

We believe successful AI implementation requires more than technology. It takes a deep understanding of business problems, thoughtful solution design, strong client partnerships, and disciplined execution.

We're looking for a hands-on AI Solutions Consultant who can connect business objectives with technical possibilities and help our US clients move from ideas to implementation.

About the RoleAs an AI Solutions Consultant & Client Delivery Lead, you will serve as a primary point of contact for clients, taking ownership of engagements from discovery and solution design through implementation, delivery, and continuous improvement.

You will work directly with US clients to understand their business goals, evaluate existing processes, identify opportunities for AI and automation, and translate requirements into clear solution architectures, technical roadmaps, project plans, and measurable outcomes.

You will collaborate closely with AI engineers, software developers, product teams, and business stakeholders to ensure that solutions are technically sound, commercially viable, and aligned with client expectations.

This role is ideal for someone who combines consulting and communication skills with practical experience in AI projects. You should be equally comfortable leading a client workshop, discussing an AI agent architecture with engineers, presenting a project roadmap, and resolving an implementation roadblock.

We are looking for a problem solver and trusted client advisor, not someone who only creates presentations and strategy documents.

Key Responsibilities1.

Client Relationship

Management

- Serve as the primary point of contact for assigned US clients and build trusted, long-term relationships.
- Lead client discovery calls, requirement-gathering sessions, workshops, solution reviews, and project status meetings.
- Understand client business objectives, operational challenges, existing systems, and desired outcomes.
- Communicate project progress, risks, dependencies, decisions, and next steps clearly to client stakeholders.
- Manage expectations, resolve concerns, and maintain alignment between client requirements and delivery commitments.
- Identify opportunities to expand existing engagements through additional AI use cases, automation initiatives, and technology improvements.

2. AI Consulting and Solution Design
- Identify and evaluate business processes that can benefit from AI, intelligent automation, and AI-powered applications.
- Translate business requirements into solution concepts, functional specifications, use cases, and implementation plans.
- Design AI solution approaches involving AI agents, large language models (LLMs), retrieval-augmented generation (RAG), conversational AI, workflow automation, and system integrations.
- Evaluate build-versus-buy options, technology choices, feasibility, implementation complexity, and business impact.
- Work with engineering teams to define solution architecture,



integration requirements, data dependencies, security considerations, and technical roadmaps.

- Project and Delivery Management
- Own the day-to-day coordination and successful delivery of client projects from initiation through deployment.
- Translate approved scopes into milestones, deliverables, timelines, responsibilities, and acceptance criteria.
- Coordinate cross-functional teams across AI engineering, software development, product, QA, and other relevant functions.
- Monitor project progress, identify delivery risks, remove blockers, and drive timely resolution of technical and operational issues.
- Manage scope changes, dependencies, resource requirements, and client approvals.
- Ensure deliverables meet agreed quality standards and business requirements.
- Lead project reviews, demonstrations, user acceptance testing, deployment coordination, and post-launch improvement discussions.
- Maintain explicit project documentation, decision logs, action items, and status reports.

4. Technical Collaboration and Problem-Solving
- Engage in meaningful technical discussions with engineers and architects to evaluate proposed solutions.
- Understand AI application architectures, APIs, data flows, integrations, model selection, and deployment considerations.
- Challenge assumptions, investigate implementation issues, and help teams identify practical solutions to technical roadblocks.
- Participate in proof-of-concept development, solution validation, and technical feasibility assessments where required.

5. Business Cases and Measurable Outcomes
- Develop business cases that connect AI initiatives to operational efficiency, revenue growth, customer experience, cost reduction, or risk mitigation.
- Define success metrics and baseline measurements before implementation.
- Estimate implementation costs, expected benefits, potential ROI, and ongoing operational requirements.
- Track post-deployment performance and identify opportunities to improve adoption, accuracy, efficiency, and business value.
- Help clients prioritize AI initiatives based on business impact, feasibility, risk, and implementation effort.

6. Presales and Solution Advisory
- Support sales conversations by participating in discovery calls, technical discussions, and solution presentations.
- Help translate client challenges into compelling proposals, statements of work, solution approaches, and effort estimates.
- Present technical concepts in clear business language to executives and non-technical stakeholders.
- Help clients understand what AI can realistically accomplish, where human intervention remains necessary, and how to approach implementation in phases.

Required Qualifications
- 5–10 years of relevant professional experience in technology consulting, solution consulting, business analysis, technical project management, AI implementation, or digital transformation. Candidates with exceptional hands-on AI delivery experience may be considered with fewer years.
- Demonstrated involvement in at least two AI, generative AI, AI automation, or intelligent application projects,



preferably taken beyond proof of concept into production or live deployment.
- Experience working directly with clients to understand requirements, recommend solutions, manage expectations, and coordinate delivery.
- Strong understanding of AI applications, including LLM-based solutions, AI agents, RAG, conversational AI, or AI-enabled business workflows.
- Ability to translate business problems into technical requirements and actionable implementation roadmaps.
- Experience coordinating developers, engineers, architects, QA teams, and other cross-functional stakeholders.
- Strong analytical, problem-solving, communication, presentation, and stakeholder management skills.
- Understanding of project planning, scope management, risk identification, effort estimation, and delivery governance.
- Ability to discuss technical trade-offs and implementation challenges with engineering teams.
- Strong written and spoken English, with the confidence to lead professional discussions with US clients.
- Ability to manage multiple engagements, prioritize competing demands, and take ownership of outcomes.

Preferred Technical ExperienceExperience in one or more of the following areas will be an advantage:

- AI agents and agentic workflows.
- Generative AI applications, LLM integrations, RAG, embeddings, and vector databases.
- Frameworks and platforms such as LangChain, LangGraph, LlamaIndex, OpenAI APIs, Anthropic APIs, or equivalent technologies.
- Workflow automation tools such as n8n, Make, or Zapier.
- Conversational AI and voice-enabled applications.
- CRM platforms such as Salesforce, HubSpot, or Zoho.
- APIs, webhooks, system integrations, databases, and cloud platforms such as AWS, Azure, or Google Cloud.
- Web and mobile application development, SaaS products, or enterprise application architecture.
- Data analytics, reporting, process intelligence, or business workflow automation.
- AI evaluation, testing, monitoring, governance, and production deployment practices.

Important: You do not need to be an expert in every technology listed. We value strong technical fundamentals, hands-on project exposure, and the ability to learn and evaluate new technologies quickly. What Success Looks LikeWithin the first 60 days, you should be able to:

- Take ownership of assigned client relationships and lead discovery and project meetings independently.
- Understand client workflows and identify practical AI implementation opportunities.
- Work with engineering teams to develop clear solution approaches, technical roadmaps, and delivery plans.
- Establish effective project governance, communication, and risk management.
- Help move projects forward by resolving blockers and keeping clients and internal teams aligned.

Who Should Apply?We welcome candidates from different professional backgrounds, including:
- AI consultants who have delivered real client projects.
- Technical project managers with hands-on AI implementation experience.
- Solution architects who enjoy client interaction and business problem-solving.
- Business analysts or management consultants who have transitioned into AI and can demonstrate implementation experience.
- Software engineers or AI engineers who want to combine technical expertise with consulting, solution design, and client ownership.

The ideal candidate is curious, commercially aware, technically credible, organized, and comfortable taking responsibility when projects become challenging.

📌 AI Solutions Consultant & Client Delivery Lead (Noida)
🏢 Nectar Innovations
📍 Noida