Associate Software Engineer – Python Full Stack & AI

About Us
Maheshwari & Associates (FRN 311008E) is a Chartered Accountancy and professional financial services firm established in 1976. We have offices across Chennai, Bangalore, Mumbai, Kolkata, Pune and New Delhi. Our partners and teams serve banks, NBFCs, insurers, capital-market institutions, e-commerce, hospitals, health care, educational institution, supply chain, and manufacturing companies. Our work spans Risk assurance, Risk advisory and IT/cyber risk assurance. We offer a structured environment that values professional development, performance and innovation.
Our Cyber Assurance practice builds technology-led offerings, including a FAIR-based Cyber Risk Quantification (CRQ) program. The program translates cyber risk into financial terms for boards and regulators. We are building an in-house engineering capability to complete this program and to drive AI-led automation across the firm.
Role Summary
You will be a hands-on full stack developer on a small, focused team, working directly with partners and domain experts. You will design, build and maintain the web applications, data pipelines and AI tools behind our CRQ program and internal automations. You will own features end to end, from requirement to deployment, and learn how financial, regulatory and risk concepts become working software.
What You Will Do
Build and extend Python applications, including quantitative models, data processing, and automated Excel, Word and PowerPoint reporting.
Develop front-end interfaces and back-end REST APIs for internal tools and client-facing solutions.
Integrate LLM APIs into workflows such as document drafting, data extraction, research support and process automation.
Build workflow automations connecting business applications, APIs and databases.
Write tests, use Git, take part in code reviews, and document your work so results are reproducible and reviewable.
Handle client and firm data with strict confidentiality and security discipline.
Qualifications – Must Have
1–3 years of software development experience, or a strong portfolio of shipped projects for exceptional freshers.
Strong Python fundamentals, including a web framework (Django or Flask) and data libraries (pandas/NumPy).
Working experience with a modern front-end stack: HTML, CSS, and JavaScript/TypeScript with React or Angular.
Experience with SQL databases (PostgreSQL/MySQL), REST APIs, and basic software design principles.
Hands-on experience calling LLM APIs (for example Anthropic Claude, OpenAI or open-source models) in a project you can show us.
Comfort with numbers: basic statistics and probability, and a willingness to learn how to read financial statements.
Clear English communication, and the discipline to verify your own work, including AI-generated code.
Bachelor's degree in Computer Science, IT, Engineering, Mathematics or a related field, or equivalent practical experience.
Good to Have
Exposure to BFSI (banking, insurance, NBFCs, capital markets) or manufacturing, through work, internships or projects.
Familiarity with cybersecurity, risk frameworks or regulatory compliance.
Experience with simulation or statistical modelling, or with document automation (openpyxl, python-docx, python-pptx).
Machine learning fundamentals (scikit-learn, PyTorch or TensorFlow).
Experience with workflow automation tools (such as n8n) or cloud deployment.
Prior work in professional services or consulting.
Why Join Us
Build a domain-rich product (quantified cyber risk for boards and regulators), not generic CRUD applications.
Learn finance, risk and regulation directly from Chartered Accountants and cyber assurance professionals.
Early ownership in a small team, with visible impact on client deliverables.
Exposure to leading AI tools and enterprise clients across BFSI and manufacturing.
Selection Process
Shortlisted candidates will complete a short practical exercise before the final interview. Please include with your application:
1. Your resume.
2. A GitHub or portfolio link.
3. Three to five lines on one project you built using an LLM API, including what went wrong and how you fixed it.
Applications without a work sample or link will not be considered.

Work arrangement
No