About The Role :

We are building a next-generation ESG (Environmental, Social & Governance) data acquisition, analytics and reporting platformavailable via web and mobile for both Prosumer and Enterprise users. Were looking for a hands-on Software Engineer who can work as an individual contributor across the stack, collaborate with small internal teams and external vendors, and deliver a high-quality, scalable product.

This role is for someone who loves solving real-world data challenges, delivering clean UX, and leveraging newer technologies like vector search, hybrid search, embeddings and AI-assisted workflows to bring efficiency, accuracy, and consistency into an ESG ecosystem.

Key Responsibilities :

1. Design and develop modules for :

- Data acquisition from APIs, user inputs, IoT, web and third-party sources

- Data normalization, validation, analytics and scoring pipelines

- Secure, high-performance storage and retrieval

- Build intuitive and responsive web & mobile interfaces using Next.js + React.js (PWA or React Native experience is a plus)

- Develop backend services and APIs in PHP and Python

2. Implement intelligent search using :

- Vector search, Hybrid search, semantic ranking, metadata filtering

- Work directly with UX, Data teams and vendors to integrate models, data sources and UI components

- Ensure security, access control, audit logs, and compliance with ESG data standards

- Maintain CI/CD pipelines, automated testing and clear technical documentation

- Operate as a true individual contributor : hands-on development, debugging, testing and deployment

Required Technical Skills :

1. Languages & Frameworks :

- PHP (Laravel or Symfony), Python

- Next.js, React.js, JavaScript/TypeScript

2. Search & AI :

- MongoDB vector search optimization ($vectorSearch, HNSW tuning, hybrid search)

- Performance benchmarking & query optimization for real-time analytics

- Hybrid search combining semantic + keyword relevance

- Good to have Experience with vector databases (Pinecone, Weaviate, Milvus, Qdrant, etc.)

- Migration strategy planning from MongoDB to specialized vector databases

- Exposure to NLP, embeddings or RAG workflows is a strong advantage

3. Databases :

- MongoDB, PostgreSQL/MySQL

4. Architecture :

- Microservices, REST APIs, GraphQL

- Docker / Kubernetes, Git, CI/CD pipelines

5. Mobile :

- Responsive designs, PWA or React Native (nice to have)

How You Work :

- Comfortable in a small, fast-moving product team

- Ability to collaborate with vendors (data sources, model providers, UI/UX partners)

- Takes complete ownership as an individual contributorfrom idea to deployment

- Strong communication and problem-solving mindset

Key KPIs for Success :

- Reduction in manual data processing time through automation & ML

- Improved accuracy of scoring & benchmarking

- Page and API response times consistently meeting SLA targets

- Uptime, error rate, and performance within defined SLOs

- Successful delivery of product modules within sprint timelines

- User satisfaction measured through reduced support tickets & positive UX feedback

- Search results relevance improvements through vector/hybrid search deployments

Preferred Qualifications :

- Experience in data analytics, or enterprise data systems

- Exposure to LLM-based document parsing, entity extraction or summarization

- Cloud platform hands-on experience (GCP, AWS or Azure)

- Security-first mindsetencryption, RBAC, secure storage

- Interest in ESG, Sustainability analytics (Good to have)