Software Developer – II

Posted 11 Days Ago
Be an Early Applicant
Bangalore, Bengaluru Urban, Karnataka
In-Office
Mid level
Artificial Intelligence • Software • Generative AI
The Role
Develop and maintain scalable backend services and APIs, manage database engineering, ensure code quality and system reliability, and collaborate with product teams.
Summary Generated by Built In

About Wokelo:

Wokelo is an LLM agentic platform for investment research and decision making. We automate complex research and analysis tasks traditionally performed by humans. Our platform is leveraged by leading Private Equity firms, Investment Banks, Corporate Strategy teams, Venture Capitalists, and Fortune 500 companies.

With our proprietary agentic technology and state-of-the-art large language models (LLMs), we deliver rich insights and high-fidelity analysis in minutes—transforming how financial decisions are made.

Headquartered in Seattle, we are a global team backed by renowned venture funds and industry leaders. As we rapidly expand across multiple segments, we are looking for passionate individuals to join us on this journey.

Requirements:

  • Experience: 2–4 years of hands-on experience building and maintaining backend systems in a production environment, preferably for SaaS or workflow-driven platforms.

  • Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or an equivalent technical field (or equivalent practical experience).

Core Backend Competencies

  • Python & Django (DRF): Strong proficiency in Python and Django Rest Framework, including request/response lifecycle, serializers, permissions/auth, middleware, and REST best practices.

  • API Engineering: Proven experience designing and shipping scalable, secure, well-versioned APIs, including:

    • Pagination, filtering, sorting, rate limiting, idempotency, and backwards compatibility

    • Authentication/authorization patterns (JWT/OAuth/session-based as applicable)

    • API documentation practices (OpenAPI/Swagger preferred)

    • Database & ORM Expertise: Solid experience with Django ORM and relational data modeling, including transaction handling and integrity constraints.

SQL & PostgreSQL

  • Strong SQL proficiency with PostgreSQL, including:

    • Complex query writing (joins, subqueries, CTEs, window functions, aggregations)

    • Schema design (normalization/denormalization tradeoffs), constraints, migrations

    • Indexing strategies and query planning (EXPLAIN/ANALYZE), performance tuning

    • Troubleshooting production database issues (slow queries, locks, concurrency, connection pooling)

Software Engineering Quality (Must-Have)

  • Design & Maintainability: Strong understanding of backend architecture and design principles (clean interfaces, modularity, separation of concerns, sensible abstractions).

  • Testing: Experience writing and maintaining tests (unit/integration), and familiarity with test automation practices in CI pipelines.

  • Code Quality: Comfortable with code reviews, refactoring, linting/formatting standards, and enforcing engineering best practices.

Ownership & Collaboration

  • Ability to own features end-to-end—requirements understanding, technical design, implementation, rollout, monitoring, and iteration.

  • Strong collaboration skills with product, ML, and frontend teams; able to communicate tradeoffs clearly and move from ambiguity to execution in a fast-paced setting.

Preferred / Nice-to-Have

  • LLM / NLP Exposure: Familiarity with ML/NLP systems or LLM-enabled workflows (prompting, evaluation, retrieval concepts, or production integration patterns).

  • Cosmos DB: Experience with Azure Cosmos DB, including partitioning strategies, data modeling, and query/performance considerations.

  • Node.js: Working knowledge of Node.js for service development, integrations, tooling, or microservices; familiarity with async patterns and runtime performance basics.

Bonus

  • Familiarity with cloud deployment and operations basics (logging/metrics/tracing, CI/CD, containers, environment/config management).

Responsibilities:

  • Backend Development & Delivery

    • Design, build, and maintain scalable backend services and REST APIs using Python and Django Rest Framework.

    • Translate product and technical requirements into clean, maintainable implementations, with clear ownership from development through deployment.

    • Implement robust authentication/authorization, validation, error handling, and API versioning to support external and internal consumers.

  • Feature Ownership & Assigned Work

    • Own assigned features and engineering tasks end-to-end: technical design, estimation, implementation, testing, rollout, and post-release verification.

    • Break down larger initiatives into deliverable milestones; proactively surface risks, dependencies, and tradeoffs.

    • Collaborate closely with Product, ML, and Frontend to deliver core platform capabilities on schedule.

  • Database Engineering & Maintenance (PostgreSQL + ORM)

    • Design and evolve relational schemas; write and optimize SQL queries and ORM access patterns for correctness and performance.

    • Manage database migrations, schema changes, and data backfills with minimal downtime and safe rollback strategies.

    • Perform ongoing database maintenance activities including indexing, query tuning (EXPLAIN/ANALYZE), monitoring slow queries, and improving performance and concurrency behavior.

    • Ensure data integrity via constraints, transactional workflows, and appropriate isolation/locking strategies.

  • Operational Excellence & Production Support

    • Provide production support for backend services: triage incidents, debug issues, identify root causes, and implement permanent fixes.

    • Monitor service health using logs/metrics/traces; improve observability through structured logging, meaningful alerts, and dashboards.

    • Participate in on-call or incident response processes (as applicable), ensuring timely communication and resolution.

    • Conduct post-incident reviews and implement preventative improvements to reduce recurrence.

  • Platform Reliability & Maintenance Activities

    • Maintain and improve existing systems: refactoring, dependency upgrades, security patches, and performance optimizations.

    • Address technical debt systematically while balancing new feature development and stability.

    • Implement and maintain background jobs/workers, scheduled tasks, and integrations as required by the platform.

  • Quality, Testing & Engineering Standards

    • Write and maintain unit, integration, and regression tests to ensure reliability and prevent breakages.

    • Drive adherence to engineering best practices: code reviews, documentation, consistent style, and secure coding standards.

    • Ensure changes are production-ready through CI checks, staged rollouts, and verification plans.

  • Team Contribution

    • Participate actively in code reviews, architecture discussions, and technical planning.

    • Mentor and support junior engineers (SD-1) through reviews, pairing, and guidance on system design and debugging.

Why Join Us?

  • Work on a cutting-edge Generative AI SaaS platform shaping the future of investment research.

  • Take ownership of impactful features used by global financial leaders.

  • Exposure to LLMs, agentic systems, NLP, ML Ops, and scalable SaaS architecture.

  • Collaborative, high-calibre global team with strong technical leadership.

  • Full health coverage, flexible time-off, and remote-first work culture.

Top Skills

Azure Cosmos Db
Django
Django Rest Framework
Node.js
Openapi
Postgres
Python
SQL
Swagger
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The Company
HQ: Seattle, Washington
25 Employees
Year Founded: 2023

What We Do

Wokelo is a Gen-AI powered investment research platform for automating complex research workflows like due diligence, sector research, and portfolio monitoring.

Leveraging its proprietary large language model (LLM) based-agents, Wokelo automates and streamlines the curation, synthesis, and triangulation of data, delivering client-ready outputs.

Wokelo works with leading private equity funds, investment banks, consulting firms, and corporates to make data-driven decisions.

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