Software Development Engineer

Key Responsibilities:

• Scalable System Design: Architect and build highly scalable, secure, and fault-tolerant systems that support millions of daily transactions with 99.99% uptime, while enabling continuous and rapid deployments across new business lines.

• Backend-Led Full-Stack Delivery: Design and implement features end to end — robust FastAPI backend services and well-modelled PostgreSQL data layers, with responsive React front-ends where needed — delivering cohesive, maintainable code.

• Backend & API Engineering: Build clean, well-documented REST/async APIs in FastAPI, with sound patterns for authentication/authorization, pagination, validation, and error handling, optimized for minimum latency and high throughput.

• AI / LLM (a plus): Opportunities to work on LLM-powered features — RAG, vector search, embeddings, and prompt engineering, using frameworks such as LangChain or LlamaIndex. Prior exposure is welcome but not required.

• Data Layer & Persistence: Design schemas, indexes, and query patterns in PostgreSQL (including geospatial workloads via PostGIS) to ensure optimal performance and scalability for read- and write-heavy operations.

• Data Engineering: Build and operate data pipelines that move, transform, and serve data at scale — ETL/ELT with Airflow, Spark, and Kafka, dbt models, and cloud data warehouses — across both batch and streaming workloads.

• Cloud & Infrastructure: Build, deploy, and operate services on AWS, using managed services, containers, and infrastructure-as-code, with attention to cost, security, and observability.

• Performance Optimization: Identify and address bottlenecks across the stack - frontend rendering, API latency, database queries, caching - using profiling, indexing, partitioning, and parallelization to keep workloads fast at scale.

• Quality & Reliability: Produce quality code that raises the bar for the whole team on quality and speed. Implement automated testing, CI/CD, monitoring, alerting, and rollback strategies to ensure correctness and resilience in production.

• Engineering Planning & Design: Contribute to the long-term technology roadmap, participate in sprint planning, retrospectives, and design reviews, and regularly communicate progress and trade-offs with stakeholders, product managers, and other developers.

• Mentorship & Team Development: Mentor and coach engineers, raise engineering standards through code reviews and design guidance, and help define career growth paths for team members.

• Collaboration & Communication: Coordinate across teams to understand user requirements and provide technical solutions. Communicate findings, insights, and technical decisions effectively to both technical and non-technical stakeholders.

Requirements:

• Must-have:

• Bachelor's or Master's degree in Computer Science or a related field.

• 7+ years of software development experience, with a track record of deploying and operating systems in production.

• Proven experience designing highly scalable, distributed systems with high availability and low latency.

• Strong backend and API engineering in Python (FastAPI) — REST / GraphQL APIs, microservices, and relational databases (PostgreSQL, MySQL).

• Hands-on experience building and operating applications on AWS (compute, storage, networking, managed databases, containers); exposure to GCP or Azure is a plus.

• Solid understanding of system design, API design, RDBMS and NoSQL databases, caching, and asynchronous/event-driven patterns.

• Strong fundamentals in data structures, algorithms, testing, CI/CD, containerisation (Docker / Kubernetes), and observability.

• Strong knowledge of Scrum or Agile frameworks such as Kanban, Crystal, etc.

• Strong analytical and problem-solving skills, with the ability to work on large, complex systems.

• Strongly preferred — experience in one or more of the following:

• Data engineering — building and operating data pipelines at scale: ETL / ELT, Apache Spark, Airflow, Kafka, dbt, and cloud data warehouses (Snowflake, BigQuery, Redshift), across batch and streaming, with strong SQL.

• Good-to-have:

• Exposure to AI / LLM engineering — building LLM-powered features and retrieval systems (RAG, LangChain or LlamaIndex, vector databases such as Pinecone, Weaviate, Chroma, or FAISS, embeddings, tool/function calling, and prompt engineering), using model APIs such as OpenAI, Anthropic, or Hugging Face.

• Experience with GIS / geospatial development — PostGIS and spatial queries, geospatial formats/standards (GeoJSON, Shapefile, KML, GeoParquet, STAC), and libraries such as GDAL, Rasterio, GeoPandas, Shapely, Fiona, Xarray.

• Familiarity with mapping/visualization libraries (Mapbox, MapLibre, Leaflet) and distributed execution frameworks (Dask, Ray).

• Experience with cloud-native and infrastructure-as-code practices (containers, Kubernetes, Terraform).

Benefits:

• Medical health cover for you and your family, including unlimited online doctor consultations
• Access to mental health experts for you and your family
• Dedicated allowances for learning and skill development
• Comprehensive leave policy with casual leaves, paid leaves, marriage leaves, bereavement leaves

Interview Process:

• Intro call
• Assessment
• Interview rounds (ideally up to 3-4 rounds)
• Culture Round / HR round