Description:

Job Location: Kolkata

Job Timings: US Central Time (40/hours/week)

Start: Within 30 days

Client is a woman-owned, minority-owned technology consulting firm. We help small businesses connect their systems, govern their data, and build the AI-augmented operations they can't build themselves. Our founder has 17+ years in enterprise technology, including ML leadership roles at Fortune 500 retailers. We are currently engaged with a Fortune 500 US retail client whose ML practice our founder is building from the ground up. That engagement funds the expansion of Client and work in this role.

About This Role:

You're joining as the senior engineer on a very small team. You will be the first full-time engineering hire beyond the founder, which means you set engineering standards, not just follow them. You will report directly to the founder.

Your work splits roughly 60/40.

60% of your time is Clients platform and product development. This includes extending the Django-based CRM and client delivery platform, building out productized AI services (embeddings, lead generation, data governance, document processing), integrating with partners like Stripe Connect, and building the local-language layer for the firm's Latin America expansion.

40% of your time is building reusable engineering frameworks informed by the firm's current Fortune 500 retail engagement. Think reference implementations for data pipelines, ML infrastructure, forecasting frameworks, feature store patterns. These frameworks become the Clients intellectual property and are reused across future clients. You will not access the retail client's systems, data, or infrastructure directly. The founder handles all direct client interaction; you build the reusable engineering primitives that make that work faster, cleaner, and more leverageable.

This structure is deliberate. We're not staffing a subcontractor; we're building a consulting firm's engineering bench. The work you build in year one compounds across the next 5 clients, not just one.

What You'll Do:

- Own the Django backend, CRM module, and AI services layer. Improve what works, refactor what doesn't, extend into new domains as clients come in.

- Build client delivery tooling: data migration scripts, integration connectors, ingestion pipelines, reporting dashboards.

- Productize internal automations into repeatable offerings. What the founder has built, you turn into maintainable, documented, reusable products.

- Build the local-language layer of the platform for the Brazilian and LATAM expansion.

- Set engineering standards: CI/CD, testing, deployment, observability.

On the frameworks side:

- Design reference implementations for ML data pipelines, feature engineering, forecasting, and model serving that can be deployed at enterprise retailers.

- Build anonymized-data test fixtures and synthetic datasets that let us validate these frameworks without enterprise-client access.

- Document patterns so the founder can deploy them inside a client environment with minimal rework.

- Evaluate tools, vendors, and open-source libraries so the founder can make informed buy-vs-build decisions for clients.

Must-Haves:

- 10+ years of production engineering experience, with at least 3 years in Python

- Strong Django and/or FastAPI; PostgreSQL; Redis; Celery or equivalent task queues

- Data engineering experience: Spark, Airflow or Prefect, dbt, at least one of (Databricks, Snowflake)

- ML infrastructure exposure: MLflow, feature stores, model serving, even if not daily

- Cloud platforms: comfort with AWS or GCP; able to provision and reason about infrastructure without hand-holding

- Ability to take ambiguous business problems and turn them into scoped engineering work without escalating every decision

- Written English fluency (you'll be writing design docs, not just code)

- Daily overlap with US Central Time

- Comfort with AI-assisted development (Cursor, Copilot, or similar) as part of your daily workflow, not as a novelty

Nice to Have:

- Prior work at an enterprise retailer or CPG company

- Experience building multi-tenant SaaS platforms

- Prior experience at a small consulting firm or early-stage startup (understands how to work in ambiguity)

Not Required:

- You do not need to be an ML researcher or Data Scientist. We need strong engineering with ML awareness, not the reverse.

- You do not need prior experience with Fortune 500 clients. The founder handles all enterprise client interaction.