Python Software Engineer - AI/ML Driven - WFO - Ahmedabad

Software Engineer, Analytics Pricing & Decision
Systems
On-site • Analytics • Full time • Ahmedabad, India
Description
Company Overview:
One Park Financial (OPF) is a leading Financial Technology company dedicated to empowering small
businesses by connecting them with a wide variety of flexible financing and funding options. Our
mission is to provide entrepreneurs with the working capital they need to elevate their businesses to
new heights. At OPF, we believe in working with high-performing individuals who are ready to play an
integral part in our company's expansion. We know that our success hinges on our people, and we
strive to enable them to do what they do best.
Why Join Us?
At OPF, we foster a dynamic and inclusive company culture that emphasizes collaboration, innovation,
and personal growth. Our team is composed of passionate, driven individuals who are committed to
making a difference. Here's what you can expect when you join our team:
Innovative Environment: Work with cutting-edge technology and be part of a team that is constantly
pushing the boundaries of fintech.
Professional Growth: We invest in our employees' growth with continuous learning opportunities,
training programs, and career advancement paths.
Supportive Culture: Enjoy a supportive and inclusive work environment where your ideas are valued,
and your contributions make a real impact.
Community Focus: Be part of a company that understands the importance of small and mid-sized
businesses to their communities and the nation's financial health.
High-Performing Team: Join a team of badasses who are committed to excellence and are integral to
our company's expansion and success.
We are looking for an Analytics Engineer to help build and maintain the Python pricing engine that
prices every new-business and renewal offer we make. This system decides the terms we put in front of
small businesses in real time, so when it prices correctly we grow profitably, and when it prices wrong
even by a single reference file it costs us real money at scale. You will be the second dedicated
engineer on this system, working alongside our current maintainer and reporting to the Lead Engineer,
who sets the technical direction and reviews the risky changes. Your job is to ship changes to the engine
accurately: new pricing rules, scoring updates, integrations, and the checks that keep the data it
produces correct.
This is a hands-on engineering role on a system where correctness is the product. Most changes are
edits to reference data rate tables, scorecards, modifiers as much as they are code, so we need

someone careful by instinct: reads a specification closely, thinks through how a change flows into the
final offer, and tests before shipping rather than after. You will not be owning the whole system alone or
leading a team; you will be growing into a deep, trusted co-maintainer of the engine, with the Lead
Engineer and our current maintainer investing in you to get there.
The pricing engine is where you start. As you grow into the system, the work broadens into integrating
our machine-learning models into production, building the internal analytics applications other teams
rely on, and owning the data checks those applications depend on. We are looking for someone early in
their career who is hungry to become excellent at building high-stakes, business-logic-heavy systems,
and who wants to grow with a team building an analytics platform from the ground up.
We are an AI-forward company, and we expect our engineers to work that way. We want someone who
leans on modern AI and LLM tooling to build, test, and ship faster and sharper, not someone who does
things the slow, manual way.
We want to work with high-performing people who will play an integral part in transforming the
company. We understand one thing: it all comes down to working with creative and committed people
and enabling them to do what they do best.
Responsibilities:
Build and maintain features in our Python-based pricing and decision engine, deployed on AWS
(FastAPI, ECS/Fargate, DynamoDB, S3, Lambda, SQS, CloudWatch), working under the direction and
code review of the Lead Engineer.
Implement new pricing rules and scoring updates from clear specifications maintaining the offer
grids, modifiers, and rules that set terms, rates, origination fees, and offer sizing and verify each
change produces the right offer before it ships.
Treat a mispriced offer as the serious incident it is: test your changes thoroughly, reason about how
an edit flows through the offer math, and never ship a pricing change you have not proven correct.
Help keep the data the engine writes to DynamoDB and S3 correct and complete per-decision
audit records, experiment history, and the versioned reference files that drive pricing and build
the validation and reconciliation checks that catch problems early.
Support the integrations between the engine and the systems around it: the sales platform it prices
for, the CRM, and the external credit and bank-data providers.
Help keep the engine reliable and observable, and support the health dashboard the team uses to
monitor it in production.
Write clean, tested, reviewable code, and grow into deeper ownership of parts of the system over
time.
Collaborate with Data Science, QA, DevOps, and the sales-platform team as you take changes from
specification to production.
Use modern AI and LLM tooling to speed up your own work, from prototyping to documentation to
testing.

Requirements
Qualifications:
24 years of professional Python development, including building or maintaining real applications
and services, not just scripts or notebooks.
Solid fundamentals in writing clean, tested, readable code, and a willingness to have your work
reviewed and to learn from that review.
Some experience with REST APIs (FastAPI, Flask, or similar), or a clear ability to pick them up quickly.
Working familiarity with AWS, or strong fundamentals and genuine eagerness to learn our stack
(ECS/Fargate, DynamoDB, S3, Lambda, SQS, CloudWatch). Deep production AWS operations
experience is not expected on day one.
Comfort with SQL and working with structured data files such as CSV and Parquet.
Care for correctness in business-logic-heavy code: the instinct to read a rule carefully, implement it
exactly, and check the result rather than assume it worked. This matters to us more than years on a
rsum.
Exposure to data validation or modeling frameworks such as Pydantic is a plus, along with an
interest in building QA and reconciliation checks rather than trusting writes blindly.
Strong communication able to ask good questions, follow a specification, and flag when
something looks wrong.
Eager to learn, coachable, and comfortable owning tasks end to end with guidance from a senior
engineer.
Comfort using modern AI and LLM tools to make your own work more efficient.
Nice to have:
Background or coursework in financial services, lending, or pricing systems.
Exposure to DynamoDB or other NoSQL stores, and to versioned data in S3 (Parquet, partitioning).
Any experience integrating machine learning or analytical model outputs into an application
feature engineering, scoring logic, or model deployment.
Exposure to A/B testing or experimentation and the idea of keeping experiment data clean.
Experience with CRM or platform APIs such as Salesforce or HubSpot.
CI/CD and containerized deployments (Docker, ECS).
Analytics-engineering tooling such as dbt or Airflow.
Front-end familiarity (Next.js, TypeScript) for the admin and monitoring dashboard.
Experience building with AI infrastructure and agents (RAG, LangChain, LangGraph, Agents SDK).
Internal leveling note remove before posting. This is the second engineer on the pricing engine and the
intended growth-path backup to our current maintainer. Targeted at 24 years: strong fundamentals and
correctness instincts over breadth of senior experience. Reports to the Lead Engineer, learns the system under

the Lead and the current maintainer, and grows into a trusted co-maintainer over 612 months. It does not
carry team leadership, sole ownership of risky changes, or the platform-vision scope those sit with the
Lead Engineer role.
One Park Financial • Analytics • Software Engineer, Analytics Pricing & Decision Systems