Role Overview

As a Forward Deployed Engineer (FDE) within the Analytics Business Unit (BU), your mission is to take high-impact ideas, prototypes, and MVPs created by data scientists, analysts, and business leaders, and turn them into scalable, production-grade applications.

Your work will span a range of data-intensive systems, including full-stack internal platforms and GenAI-driven applications, such as a natural language insights chatbot that lets stakeholders query complex business data for "what, why, how, and when" answers. You will refactor prototype code, design resilient architectures, and take internal tools from early build through to full production.

Mandatory Job Link https://forms.gle/yptTEC8K65DjT9TK7

Engagement Structure

This role starts as a three-month contract, which serves as a probation period.

- You will not be starting from scratch. Acadia has already made significant progress on the product you'll own.
- During the three-month period, you are expected to take that work and ship it as a complete, production-ready product.
- At the end of the three months, based on performance, you will be confirmed into a full-time role.

Key Responsibilities

- MVP to Productionization: Take early-stage applications, internal tools, and prototypes (e.g., Streamlit, Dash, Python scripts, raw models) developed by the Analytics team and re-engineer them into secure, performant, enterprise-grade products.
- Full-Lifecycle Application Engineering: Design, build, and deploy robust APIs, microservices, and user interfaces tailored to power internal and stakeholder-facing analytics tools.
- GenAI & RAG Systems: Architect and ship production-ready RAG (Retrieval-Augmented Generation) pipelines, vector search systems,



and Text-to-SQL logic for natural language interface projects.
- Architecture & Scalability: Optimize data flows, system performance, vector retrieval, and database queries to ensure applications scale seamlessly under enterprise workloads.
- DevOps, Guardrails & Reliability: Establish CI/CD pipelines, automated testing, caching, and observability, including LLM evaluation and safety guardrails to ensure deterministic accuracy and hallucination prevention.
- Embedded Collaboration: Work side-by-side with data scientists, analysts, and BU product leaders to translate raw business requirements into transparent technical specifications and maintainable software.

Requirements

- Application Engineering: Minimum of 3–4 years spent architecting web platforms and robust APIs. You possess deep technical mastery in modern backend environments (such as Python/FastAPI/Django, Go, or Node.js) paired with a working knowledge of frontend ecosystems like React or Next.js.
- GenAI & RAG Stack: Hands-on experience building and deploying RAG pipelines, working with vector stores (e.g., Pinecone, Qdrant, Milvus, pgvector), and integrating LLM orchestration frameworks (e.g., LangChain, LlamaIndex, or native APIs).
- Track Record of Delivery: Proven experience refactoring script/prototype code into reliable, maintainable software architectures.
- Cloud & Infrastructure: Hands-on experience with containerization (Docker, Kubernetes),



cloud platforms (AWS, GCP, or Azure), and deployment automation (CI/CD).
- Cross-Functional Communication: Excellent interpersonal skills with the ability to partner effectively with non-traditional software developers (e.g., data scientists, business analysts) to bridge data logic with product engineering.

Preferred Qualifications

- Experience with semantic layers (e.g., dbt Semantic Layer, Cube) or agentic frameworks (e.g., LangGraph) for complex multi-step analytical reasoning.
- Familiarity with LLM observability, tracing, and evaluation tools (e.g., LangSmith, LangFuse, TruLens, Ragas).
- Experience using or building developer platforms for rapid app deployment (e.g., Vercel, Heroku-style internal platforms).
- Background in building data-intensive user interfaces, embedding interactive visualization frameworks, or managing asynchronous task queues (Celery, Redis).
- Data Fluency: Solid understanding of transactional databases (PostgreSQL, MySQL), analytical data engines (Snowflake, BigQuery, Databricks), and search/caching paradigms (Redis).

Work Timings & Time Off (during the 3-month contract)

- You will be supporting US EST business hours until 2:00 PM EST, your work hours in India Standard Time (IST) will be:
- March to October (US Daylight Saving Time in effect): 2:30 PM – 11:30 PM IST
- November to February (US Standard Time): 3:30 PM – 12:30 AM IST
- These work timings apply even when the contract period ends.
- During the three-month contract, you are eligible for:
- 4 personal time-off days
- All India country-based holidays
- Full-time benefits and time-off policy apply once you are confirmed after the three-month period.

📌 Forward Deployed Engineer (India)
🏢 Acadia
📍 India