Role : Backend Engineer JD - Product Engineering

About the firm :

The firm is an early-stage startup, backed by top-tier VCs, on a mission to 10 - 100x the productivity of SAP implementation and migration teams.

Why Is This Role Special?

- Real enterprise scale : Your backend services will run inside Fortune 500 SAP landscapes - touching live finance and supply-chain data for some of the world's largest companies.

- Green-field AI : Build LLM-powered microservices, RAG pipelines, and agentic orchestration layers from scratch - no inherited tech debt.

- Proven delivery velocity : The team shipped 8 production SAP APIs in 15 days (vs. a 60-day industry standard). You will operate at that pace.

- Founder proximity : Work directly with the founders and own your domain end-to-end.

- End-to-end ownership : Schema design, API contracts, observability, Kubernetes deploys - you are accountable for the full stack below the UI.

Critical / Scale Mindset :

We build systems that plug into live SAP environments at Fortune 500 companies. A slow query, a poorly chosen index, or an unthrottled async job can cascade into real business disruption. This role is open to freshers, but you must understand why scale matters. Being able to reason about indexing trade-offs, async job design, and connection pool limits - even from coursework, personal projects, or internships - is the baseline we hire from.

Must-Have Qualifications :

- B.Tech./B.S. in Computer Science from IITs / BITS / NITs / DTU or equivalent top-tier institution.

- Fresher to 1 year of hands-on backend engineering experience.

- Strong CS fundamentals : you understand indexing, caching, and async patterns.

- Proficiency in any one backend language - Node.js, Python, Java, Go, or equivalent.

- Strong grasp of REST API design and microservices architecture.

Databases :

- Relational (PostgreSQL / MySQL) : schema design for scale, index strategy, query plan analysis, partitioning, and connection pooling.

- NoSQL (MongoDB / Redis / DynamoDB) : document modelling, sharding, TTL, and eviction policies.

- Vector databases (pgvector, Pinecone, Weaviate, or Qdrant) : embedding storage and ANN search tuning.

What Will You Do?

- Design and build production-grade AI-driven backend microservices powering SAP workflow automations.

- Integrate with SAP ecosystems (OData, CDS views, BTP, RFC/BAPI, S/4HANA APIs) and package agent capabilities as versioned, reusable SDKs.

- Own observability and reliability : wire up OpenTelemetry tracing, Prometheus metrics, and Grafana dashboards.

- Collaborate with Product, SAP consultants, and Customer Success to convert PoC insights into shippable features.

Benefits & Perks :

- Competitive cash compensation + meaningful early-employee equity in a VC-backed pre-growth startup.

- Learning budget for courses, certifications, conferences, and hardware.

- Flexible hours, generous PTO, and a culture that values deep work.