AI Product Development (Claude Expert)

Founding AI Product & Agentic Systems Architect Specialisation: Claude AI | Agentic AI | Multi-Agent Architecture | SaaS | AI Automation | Revenue Intelligence Company: TechBliss Solutions / 6OAM Location: Noida / Delhi NCR, India (Hybrid / On-site preferred) Employment: Full-time Experience: 4–8 years in software/product engineering, with demonstrable production AI product experience Seniority: Senior / Founding Team Member About TechBliss Solutions & 6OAM TechBliss Solutions is a technology and digital growth company helping businesses leverage cloud technology, AI, automation, digital marketing and intelligent business systems. Through our AI-powered business growth platform, 6OAM, we are building an ecosystem of intelligent solutions that help businesses acquire customers, improve productivity, automate operations, increase conversions and scale revenue. We are not looking to become another AI services company that simply implements third-party tools. Our ambition is to build our own portfolio of AI-powered products by combining proprietary software, APIs, leading LLMs, third-party technologies and intelligent multi-agent architectures into unified, commercially viable solutions. We want to build an AI Product Factory. The Opportunity We are looking for a highly capable Founding AI Product & Agentic Systems Architect who can independently conceptualise, architect, develop, deploy and continuously improve AI-powered products. You will lead the development of our in-house AI product ecosystem, including: AI-powered lead generation and sales intelligence. Automated prospect discovery and lead enrichment. AI-powered SEO, AEO and GEO platforms. Social media intelligence and content automation. Competitor research and marketing strategy engines. AI-powered advertising and creative generation. Multi-agent business automation systems. AI-powered CRM, sales funnels and customer engagement. Business intelligence and revenue optimisation solutions. You will work directly with the leadership team to identify business opportunities, convert them into product specifications, develop working prototypes, deploy production-ready applications and create commercially sellable products. We need a builder, not just someone who knows how to write prompts or connect APIs. Key Responsibilities 1. AI Product Research, Architecture & Development Conceptualise and develop proprietary AI-powered SaaS products. Research existing AI tools and SaaS platforms to identify opportunities for integration, white-labelling, re-packaging or building better alternatives. Combine multiple third-party APIs, tools, models and automation platforms into unified solutions. Develop modular, scalable and reusable AI application architectures. Build web-based dashboards, client portals, workflow interfaces and product administration panels. Convert internal business requirements into repeatable commercial products. Maintain product documentation, architecture diagrams, APIs and development roadmaps. Evaluate build-versus-buy decisions based on cost, performance, reliability and commercial potential. 2. Claude AI & Agentic AI Development Demonstrable expertise in Claude AI, Claude API and Claude Code. Build intelligent AI agents capable of executing multi-step business processes. Design multi-agent systems where specialised agents collaborate toward a shared objective. Implement tool calling, structured outputs, memory, retrieval-augmented generation (RAG) and context management. Work with MCP servers, external tools, APIs and business applications. Develop agent orchestration, task delegation, state management and error-recovery mechanisms. Build human-in-the-loop approval systems for sensitive actions. Implement evaluation frameworks to measure agent accuracy and reliability. Optimise token consumption, inference costs, latency and model selection. 3. Business Revenue Growth OS Lead the development of our flagship AI-powered Business Revenue Growth Solution. Build an integrated system covering: A. Market & ICP Intelligence Identify ideal customer profiles (ICPs). Discover high-intent industries, companies and business categories. Identify buying signals and trigger events. Research decision-makers and stakeholders. Analyse company websites, technology stacks, market positioning and business gaps. Generate account-level opportunity scores. B. Lead Discovery & Extraction Discover business leads from approved data providers, directories, search APIs and other permitted sources. Extract publicly available business information through compliant methods. Discover relevant LinkedIn engagement opportunities, including posts, commenters and business discussions through permitted integrations and approved data sources. Identify prospects engaging with competitor content or relevant industry discussions. Import and process CSV, CRM and third-party lead databases. Build reusable lead-discovery workflows for different industries and services. C. Lead Enrichment & Intelligence Enrich company and professional profiles. Identify business websites, company size, industry and relevant contact information. Discover decision-maker roles and publicly available business contact channels. Analyse websites for SEO, website conversion, social media and technology gaps. Generate AI-powered prospect intelligence reports. Identify relevant products and services to pitch to each prospect. Assign lead scores based on intent, fit, budget indicators and engagement. D. Omnichannel Outreach Integrate email, WhatsApp Business API, LinkedIn-approved workflows and CRM. Develop personalised outreach sequences. Build automated follow-up and nurture journeys. Generate personalised messages based on prospect intelligence. Detect replies, classify intent and recommend next actions. Automate appointment scheduling and sales handovers. Build campaign analytics and conversion tracking. 4. AI-Powered Marketing Intelligence Build products and agents for: AI marketing strategy generation. Industry and niche research. Audience analysis. Customer persona creation. ICP discovery. Competitor analysis. SWOT analysis and positioning. Marketing funnel recommendations. Channel selection and campaign planning. Budget allocation recommendations. Marketing performance analysis. Content strategy and editorial calendars. Campaign performance prediction and optimisation. The objective is to move beyond AI-generated suggestions and develop systems that can research, analyse, recommend, execute approved actions and measure actual outcomes. 5. SEO, AEO & GEO Intelligence Products Develop intelligent systems that can: Perform comprehensive technical SEO audits. Analyse keyword opportunities and search intent. Discover competitor keywords and ranking gaps. Generate topical maps and content clusters. Conduct backlink and authority gap analysis. Identify indexing and technical issues. Generate SEO briefs and optimised content. Monitor brand visibility in AI search engines. Analyse brand mentions and citations across ChatGPT, Gemini and other answer engines. Identify AEO and GEO content gaps. Recommend structured data and schema improvements. Track content performance and organic visibility. Generate actionable SEO/AEO/GEO task lists. Integrate with Google Search Console, Analytics and other approved APIs. Build an AI SEO/GEO cockpit rather than another basic AI blog-writing application. 6. Social Media & Content Intelligence Develop AI products for: LinkedIn Industry and competitor content monitoring. Identify relevant posts, discussions and engagement opportunities. Analyse high-performing content. Discover potential prospects and buying signals. Generate LinkedIn content and personalised responses. Build content calendars and performance dashboards. Manage approved publishing and engagement workflows. Instagram Competitor account intelligence. Trend and content analysis. Reel and carousel idea generation. AI-powered captions, hooks and hashtags. Creative and content calendar generation. Comment and enquiry classification. Lead capture through approved Instagram integrations. DM automation and lead qualification. YouTube Competitor channel intelligence. Video topic and keyword discovery. Content gap analysis. Video script and title generation. Thumbnail concept generation. Shorts and long-form content repurposing. Performance analysis and optimisation recommendations. Other Social Platforms Facebook, X, Pinterest and other relevant channels. Platform-specific content generation and scheduling. Multi-platform content repurposing. Unified social performance analytics. 7. AI Creative & Advertising Intelligence Build products for: AI-powered advertising creative generation. Static ad and carousel generation. Video advertisement concept development. AI video scripts and storyboards. Product image generation and enhancement. Creative variations for different audiences. Brand guideline enforcement. Ad copy, headlines, hooks and CTAs. Competitor ad research using approved public data sources. Creative performance analysis. A/B testing recommendations. Landing-page and advertisement alignment analysis. Automated creative production pipelines. Integrate relevant image, video, voice and design APIs rather than unnecessarily rebuilding specialised generation engines. 8. Multi-Agent Automation Framework Design a reusable framework where multiple specialised agents can collaborate. Examples: Research Agent ICP Agent Lead Discovery Agent Lead Enrichment Agent Competitor Intelligence Agent SEO Agent Content Agent Creative Agent Outreach Agent CRM Agent Sales Qualification Agent Reporting Agent Strategy Agent Each agent should have a clearly defined role, inputs, outputs, tools, permissions, memory and measurable success criteria. Agents should communicate through a reliable orchestration layer, share relevant context and work toward a common business objective. 9. Productisation & Commercialisation Convert internal automation workflows into reusable commercial products. Build multi-tenant SaaS applications. Create client-specific workspaces and configurable workflows. Implement subscription plans, usage limits and billing integrations. Develop white-label and rebrandable solutions. Create reusable templates for different industries. Build APIs and integrations for third-party applications. Prepare product demonstrations for the sales team. Work with the sales and marketing teams to identify customer requirements. Continuously improve products using client feedback and usage analytics. 10. Internal AI Enablement Automate our own business processes across: Sales prospecting and follow-ups. Proposal generation. CRM updates. Client onboarding. SEO and digital marketing delivery. Social media management. Reporting and analytics. Customer support. Project management. Internal knowledge management. Employee productivity and management reporting. The objective is to make our existing team significantly more productive through AI-enabled systems. Required Technical Skills AI & LLM Engineering Advanced hands-on experience with Claude, Claude API and Claude Code. Strong understanding of LLM architectures and model capabilities. OpenAI, Gemini and open-source model integrations. Agentic AI and multi-agent systems. LangGraph, LangChain, LlamaIndex or equivalent frameworks. RAG, embeddings, vector databases and semantic search. MCP, tool calling and structured outputs. Prompt engineering, context engineering and evaluation. Programming & Application Development Python (strong proficiency). FastAPI or equivalent backend frameworks. JavaScript / TypeScript. Next.js / React. REST APIs, webhooks and third-party integrations. PostgreSQL and vector databases such as pgvector. Authentication, RBAC and multi-tenant architecture. Automation & Infrastructure Advanced n8n expertise. API orchestration and workflow automation. Docker and containerisation. GitHub and version control. Linux / VPS deployment. CI/CD, logging, monitoring and debugging. Cloud and self-hosted deployment experience. Data & Intelligence Web research and compliant data extraction. Data cleaning and enrichment. Scraping technology where permitted. Database design and optimisation. Data pipelines and ETL. Analytics and reporting. Preferred Technology Stack We prefer candidates who can work with a cost-efficient, modular and scalable technology stack. Claude / Anthropic API / Claude Code Google Gemini OpenAI API Ollama and open-source LLMs n8n (self-hosted) Python / FastAPI Next.js / React / TypeScript LangGraph / LlamaIndex PostgreSQL / pgvector Docker GitHub MCP APIs and webhooks Experience with additional tools and technologies is welcome. We prefer self-hosted or cost-efficient infrastructure where practical. Paid tools, APIs and infrastructure should be evaluated against their business value and approved budgets. Experience Requirements 4–8 years of software engineering, product engineering or application development experience. At least 2 years of substantial hands-on AI/LLM application development experience. Must have independently developed and deployed at least 2–3 AI-powered applications or products used by actual customers or internal business teams. Experience building agentic AI systems, not just basic chatbot applications. Demonstrable experience integrating multiple third-party APIs into a unified product. Experience developing SaaS dashboards, web applications or client-facing platforms. Experience taking a product from concept to deployment and iteration. Experience with AI automation in sales, marketing, operations or business workflows is highly desirable. Mandatory Portfolio Requirement Candidates must provide: Links to at least two AI applications or products they personally developed. A demonstration or working video of each application. Their exact contribution to the architecture, backend, frontend and AI implementation. Technologies, APIs and models used. Evidence of actual deployment and usage. A measurable result achieved by the product. GitHub repositories or technical documentation are preferred where sharing is permitted. Candidates who have only completed tutorials, prompt-engineering exercises or basic n8n integrations without building production-ready applications will not be considered suitable. Personal Attributes Strong product thinking and commercial understanding. Ability to work independently and take complete ownership. Excellent problem-solving and debugging skills. Curious about emerging AI technologies. Ability to distinguish what AI can reliably automate from what still requires human intervention. Comfortable working in a fast-moving startup environment. Able to communicate technical concepts to non-technical stakeholders. Strong documentation and knowledge-sharing habits. Focus on measurable business outcomes rather than building technology for its own sake. What Success Looks Like You will be evaluated on working products, adoption, reliability, business value and commercial outcomes. You will be expected to: Build reusable AI products rather than one-off workflows. Reduce dependency on expensive third-party subscriptions wherever technically and commercially justified. Increase the productivity of our internal teams. Enable our sales team with multiple ready-to-sell AI-powered solutions. Develop products that can be deployed repeatedly across multiple clients. Build systems that generate measurable improvements in customer acquisition, marketing efficiency and business revenue. Why Join Us? Opportunity to become a founding member of an AI product development initiative. Freedom to architect and build proprietary AI products. Direct involvement in building a commercial AI Business Operating System. Exposure to multiple industries and real business problems. Opportunity to lead a growing AI engineering team. Ownership of the technical roadmap and product development direction. Build products that can be sold to businesses in India and internationally. We are not hiring someone to experiment with AI. We are hiring someone to build products with AI that businesses will actually pay for.