Send your CVs to hr@pedasys.co.in. Mention "Full Stack" in the email subject. Lead the Engineering side development of our enterprise learning platform, ensuring robust, secure, and scalable solutions that meet the demanding requirements of our Fortune 500 clients and regulated industry partners. MUST HAVEs:⚫ Excellent spoken and written communication skills (English)⚫ The notice period with the current employer is not more than 30 days⚫ Proficient in modern JavaScript frameworks like React, Node.js and Angular⚫ Candidate should be based in Bengaluru. Office in JP Nagar. (NO WFH) Budget:⚫ 6 to 12 LPA for junior to mid-range professionals⚫ 12-24 LPA for senior professionals Responsibilities:⚫ Architect and implement scalable platform features⚫ Lead the Engineering team to work in parallel with our Q-suite and Data Science Team to streamline the development process, both in front-end Angular and React, and then in the back-end Node.js.⚫ Guide the Quality Assurance Engineer to deliver Automated testing throughout our product suite⚫ Design and implement secure API integrations, and have a base-level understanding of production security requirements⚫ Ensure platform security and performance⚫ Collaborate with the data science team on AI integration⚫ Manage technical debt and system maintenance⚫ Lead code reviews and technical documentation⚫ Implement security best practices Required Experience:⚫ 7+ years in full-stack development⚫ Technical team Lead experience.⚫ Strong background in secure coding practices⚫ Experience with enterprise-grade applications⚫ History of leading development teams⚫ Experience in regulated industries⚫ Cloud platform expertise⚫ Security-focused development background Required Experience:⚫ Modern JavaScript frameworks (React, Node.js, Angular)⚫ Cloud platforms (AWS/Azure/GCP)⚫ PostGre, MongoDB, SQL, NoSQL and Pinecone⚫ API design and implementation⚫ Security protocols and best practices⚫ CI/CD pipelines⚫ Microservices architecture
Company Description PedaSys is an EdTech start-up based in India that provides innovative educational solutions. We specialise in corporate training strategy, Learning & Development systems, Learning Outcome Management, and Digital Transformation in L&D. Our services are geared towards enhancing educational experiences through advanced pedagogic consultancy and technology-driven solutions. Role Description We need an experienced AI engineer who can build and enhance specialised agents within our production multi-agent architecture. You'll be working with a 4-person Data Science team in Bangalore, implementing RAG-based agents that handle everything from role matching and career progression to assessment and quality assurance. This is not a research role - we have clear specifications. You'll be shipping production code that serves real learners pursuing regulated qualifications. What You'll Build Immediate Projects: ● Agent #3: Career Progression Intelligence Agent (RAG + pathway ranking algorithms) ● Agent #16: Learning Specification Triangulation Agent (LO/LO/AC alignment validation) ● Agent #17: Assessor Agent (formative/summative assessment with PASS/REFER/FAIL logic) ● Agent #18: Quality Assurance Agent (meta-agent for self-critique across all agents) Enhancement Work: Core Technical Stack (Must Have 5+ Years) Primary Technologies: ● Python - All agent logic, RAG implementation, API development ● Vector Databases - Pinecone, Weaviate, Qdrant, or ChromaDB (operational production experience) ● LLM Integration - Anthropic Claude API, prompt engineering, structured outputs ● RAG Architecture - Retrieval Augmented Generation, semantic search, hybrid search ● Embedding Models - OpenAI, Cohere, or Sentence Transformers (generation and vector operations) Required Experience You Must Have: ● 5+ years Python development in production environments ● 2+ years working with vector databases in production ● 2+ years building RAG-based systems or LLM applications ● Proven experience with embedding generation and semantic search ● Experience designing and implementing APIs for agent-based systems ● Strong understanding of prompt engineering and LLM behaviour How We Work Development Approach: ● Clear specifications with detailed architecture documents ● ReACT pattern (Reasoning → Action → Critique) for all agents ● Work packages with defined deliverables and acceptance criteria ● Parallel workstreams across the 4-person DS team ● Regular integration testing between agents Current Sprint Example: ● B1: Agent #3 Core Logic (DS3, 7 days) ● B2: Integration Layer + Agent #16, #18 (DS4, 5 days) ● B3: Enhanced Agent #1 (DS3, 3 days) ● B4: Enhanced Agent #8 + #10 (DS4, 3 days) Timeline: 3-4 week sprints, production deployments Technical Environment Data Infrastructure: ● 5,000+ vectorised job descriptions across 23 sectors ● NOS Database (vectorised) ● OFQUAL Register (vectorised) ● Career Pathways Database (500+ progression routes) ● User Profile Database (operational) Why This Role Matters You'll be building AI that genuinely helps people progress in their careers. Not chatbots that hallucinate. Not marketing demos. Real production systems that: ● Match learners to 5,000+ career roles with 95% accuracy ● Map progression pathways with skill gap analysis ● Deliver regulated qualifications (OFQUAL-compliant) ● Provide formal assessments with human oversight What We Offer ● Competitive salary (based on experience) ● Remote-first culture ● Work with cutting-edge AI technology in production ● Direct impact on people's career progression ● Collaborative team that ships real products ● Opportunity to work across the full agent architecture