Technical Product Catalyst - Fintech at Cambridge Wealth (Baker Street Fintech) · Pune · 2 - 6 years · ₹8L - ₹13L / yr · Profitable · Posted 4 Nov 2026
Technical Product Catalyst - Fintech
About Us: The Next Generation of WealthTech
We're Cambridge Wealth, an award-winning force in mutual fund distribution and Fintech. We're not just moving money; we're redefining wealth management for everyone from retail investors to ultra-HNIs (including the NRI segment). Our brand is synonymous with excellence, backed by accolades from the BSE and top Mutual Fund houses.
If you thrive on building high-performance, scalable systems that drive real-world financial impact, you'll feel right at home. Join us in Pune to build the future of finance.
[Learn more: www.cambridgewealth.in]
The Role: Engineering Meets Team Meets Customer
We're looking for an experienced, hands-on Tech Catalyst to accelerate our product innovation. This isn't just a coding job; it's a chance to blend deep backend expertise with product strategy. You will be the engine driving rapid, data-driven product experiments, leveraging AI and Machine Learning to create smart, personalized financial solutions. You'll lead by example, mentoring a small, dedicated team and ensuring technical excellence and rapid deployment in the high-stakes financial domain.
Key Impact Areas: Ship Fast, Break Ground
1. Backend & AI/ML Innovation
- Rapid Prototyping: Design and execute quick, iterative experiments to validate new features and market hypotheses, moving from concept to production in days, not months.
- AI-Powered Features: Build scalable Python-based backend services that integrate AI/ML models to enhance customer profiling, portfolio recommendation, and risk analysis.
- System Architecture: Own the performance, stability, and scalability of our core fintech platform, implementing best practices in modern backend development.
2. Product Leadership & Execution
- Agile Catalyst: Drive and optimize Agile sprints, ensuring clear technical milestones, efficient resource allocation, backlog grooming and maintaining a laser focus on preventing scope creep.
- Mentorship & Management: Provide technical guidance and mentorship to a team of developers, fostering a culture of high performance, code quality, and continuous learning.
- Domain Alignment: Translate complex financial requirements and market insights into precise, actionable technical specifications and seamless user stories.
- Problem Solver: Proactively identify and resolve technical and process bottlenecks, acting as the ultimate problem solver for the engineering and product teams.
3. Financial Domain Expertise
- High-Value Delivery: Apply deep knowledge of the mutual fund and broader fintech landscape to inform product decisions, ensuring our solutions are compliant, competitive, and truly valuable to our clients.
- Risk & Security: Proactively architect solutions with security and financial risk management baked in from the ground up, protecting client data and assets.
Your Tech Stack & Experience
The Must-Haves
- Mindset: A verifiable track record as a proactive First Principle Problem Solver with an intense Passion to Ship production-ready features frequently.
- Startup Experience: Familiarity with the pace and intensity of a fast-iterating environment.
- Customer Empathy: Keeps the customer's experience in mind at all times.
- Team Leadership: Experience in leading, mentoring, or managing a small development team, driving technical excellence and project delivery.
- Systems Thinker: Diagnoses and solves problems by viewing the organization as an interconnected system to anticipate broad impacts and develop holistic, strategic solutions.
- Backend Powerhouse: 2+ years of professional experience with a strong focus on backend development.
- Python Guru: Expert proficiency in Python and related frameworks (e.g., Django, Flask) for building robust, scalable APIs and services.
- AI/ML Integration: Proven ability to leverage and integrate AI/ML models into production-level applications.
- Data Driven: Expert in SQL for complex data querying, analysis, and ETL processes.
- Financial Domain Acumen:Strong, demonstrable knowledge of financial products, especially mutual funds, wealth management, and key fintech metrics.
Nice-to-Haves
- Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Familiarity with Zoho Analytics, Zoho CRM and Zoho Deluge
- Familiarity with modern data analysis tools and visualization platforms (e.g., Mixpanel, Tableau, or custom dashboard tools).
- Understanding of Mutual Fund, AIF, PMS operations
Ready to Own the Backend and Shape Finance?
This is where your code meets the capital market. If you’re a Fintech-savvy Python expert ready to lead a team and build a scalable platform in Pune, we want to talk.
Apply now to join our award-winning, forward-thinking team.
Our High-Velocity Hiring Process:
- You Apply & Engage: Quick application and a few insightful questions. (5 min)
- Online Tech Challenge: Prove your tech mettle. (90 min)
- People Sync: A focused call to understand if there is cultural and value alignment. (30 min)
- Deep Dive Technical Interview: Discuss architecture and projects with our senior engineers. (1 hour)
- Founder's Vision Interview: Meet the leadership and discuss your impact. (1 hour)
- Offer & Onboarding: Reference and BGV check follow the successful offer.
What are you building right now that you're most proud of?

About Cambridge Wealth (Baker Street Fintech)
About
Baker Street Fintech (Product Name: Cambridge Wealth) is a Financial Products Company. We help build world-class Fintech Products for our Clients who want to manage their wealth on our platform. Founded by professionals with Experiences spanning from PwC UK to Banking and Technology firms, we are a financially stable, profitable company growing quickly!
Tech stack
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Job Description: Tech Lead – AI & Technology
Role Title: Tech Lead – AI & Technology
Location: Bangalore, India – Fully On-site
Experience: 5+ Years
Employment Type: Full-time
About the Role
We are looking for an experienced and hands-on Tech Lead to lead a small engineering team and drive the development of AI-powered applications, internal technology platforms, and modern IT solutions. The Tech Lead will be responsible for technical direction, architecture, development, code quality, team management, and end-to-end delivery of technology projects. The ideal candidate should have strong programming experience, particularly in Python and ReactJS, along with practical experience working with AI/ML technologies.
1. Technical Leadership & Team Management
- Lead and mentor a team of developers and technical team members.
- Own technical delivery across multiple projects and initiatives.
- Assign tasks, review progress, resolve technical blockers, and ensure timely delivery.
- Conduct code reviews and establish engineering best practices.
- Mentor team members and support their technical growth.
2. Software Development & Architecture
- Design and develop scalable, secure, and maintainable applications.
- Lead backend development using Python and frontend development using ReactJS.
- Define application architecture, technology choices, APIs, integrations, and development standards.
- Review technical designs and ensure high-quality implementation.
- Troubleshoot complex technical issues and drive effective solutions.
3. AI & Technology
- Lead the development and integration of AI-powered applications and solutions.
- Work with AI/ML models, APIs, LLMs, Generative AI, and related technologies.
- Evaluate emerging AI tools and technologies and identify opportunities for practical implementation.
- Collaborate with product and business teams to translate requirements into AI-enabled technology solutions.
4. Project Delivery
- Own the complete technology lifecycle from requirements and architecture to development, testing, deployment, and maintenance.
- Plan sprints, estimate development efforts, and track technical milestones.
- Work closely with cross-functional stakeholders to understand requirements and deliver solutions.
- Ensure projects meet timelines, quality standards, security requirements, and performance expectations.
5. Engineering Quality & Infrastructure
- Establish standards for coding, testing, documentation, version control, and deployment.
- Ensure applications are scalable, reliable, and secure. l Collaborate on cloud infrastructure, APIs, databases, CI/CD, and deployment processes.
- Identify opportunities to improve system performance and engineering efficiency.
Technical Skills – Must Have
- 5+ years of software development experience.
- Strong hands-on experience with Python.
- Strong experience with ReactJS / React.
- Experience leading or managing technical team members.
- Strong understanding of AI/ML and Generative AI technologies.
- Experience with APIs, databases, Git, and software development lifecycle.
- Strong understanding of application architecture and system design.
- Experience building and deploying production-grade applications.
Technical Skills – Good to Have
- Experience with LLMs, RAG, AI agents, or Generative AI applications.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Experience with Docker, CI/CD, and DevOps practices.
- Experience integrating third-party AI APIs and services.
- Experience working in startups or fast-paced technology environments.
What We Are Looking For
- Strong technical ownership and problem-solving ability.
- Ability to balance hands-on coding with team leadership.
- Excellent communication and stakeholder management skills.
- Ability to mentor developers and drive accountability within the team
- Strong interest in AI and emerging technologies.
- A proactive, ownership-driven approach with the ability to work in a fast-paced environment.
Why Join Us?
- Work on AI-powered technology with meaningful social impact.
- Lead a small, high-ownership technology team.
- Work across AI, software engineering, and modern IT infrastructure.
- Opportunity to shape technology architecture and engineering practices from the ground up.
- Collaborative and fast-moving environment with significant technical ownership.
We're hiring Drumbeat's first Senior Product Engineer to help us go to the next level.
We're not first-timers. We're the team that founded Phrasee in 2015 and grew it to more than 100 people, customers around the world, and a >$100m exit. Lots of people made lots of money, including the founding employees.
With Drumbeat, our plan is to do it all again… except this time, bigger and faster.
What is Drumbeat?
Drumbeat (www.drumbeat.com) predicts your next best action on LinkedIn, then copilots your team to turn invites, DMs and posts into pipeline.
We launched in September 2025 and have raised a £2m seed round led by a well-known VC. We're building the core team around our cofounders (Parry, Jonny and Dan) and Mohit, our Engineering Manager and Phrasee's first engineer. You'll report to Mohit.
What you'll be building on
- Setlist: a short, ordered list of the right things for each person to do today.
- Radar: predicts who each rep should connect with now, not everybody who matches a job-title search.
- Riff and AuthorDNA: help people find something worth saying, and write it in their own voice.
- Campaigns, Conversations, Backstage and Analytics: team-wide activity, replies, company knowledge and reporting.
Under the hood: Django and PostgreSQL, background jobs on Redis, LLM workflows, statistical models that learn what works, and integrations with LinkedIn and CRMs. A lot of our code is written with AI coding agents, inside a strict engineering process.
How we think about engineering
- "Human-first AI, not AI-first humans." AI agents write a lot of our code. They don't make our decisions. We want someone super smart without AI, and even smarter with it, who knows when the machine is blowing smoke.
- "Spend 55 minutes on the problem." Understand what's actually wrong before you fix it.
- "Fix the class, not the instance." Every bug is an example of something bigger. Find the pattern, and fix it everywhere it lives.
- "A check must be able to fail." A test you've never seen go red proves nothing.
- "You don't need a Ferrari to drive to the supermarket." Simplicity over cleverness, every time.
What you'll own
- Technical architecture. How Drumbeat is built, so it holds up as we add customers, features and integrations.
- Shipping features end to end. From Parry and Mohit's briefs, and turning Parry's MVPs into production features.
- Foundations. Scale, resilience (safe retries, timeouts and fallbacks when outside services wobble), cost and refactoring.
- What you build. Once it's live, it's yours: you maintain it and fix it.
- The hardest bugs. The ones nobody else can crack.
Your experience
- 8+ years as an engineer, at a product company, preferably B2B SaaS.
- Time at a smaller company, so you know how to get stuck in.
- You've owned a system in production, not just added features to one.
- Senior Python and Django: Postgres, background jobs, correctness in production.
- System architecture and refactoring.
- You direct AI coding agents well, and explain trade-offs in plain English to people who aren't engineers.
Where you'll work
Delhi / NCR. You'll be in our Delhi office some days each week, alongside Mohit.
Pay
₹40–65 lakh CTC, plus equity that vests as the company hits revenue milestones.
This is probably not a job for most people. Don't apply if you want an easy job. Apply if you want a hard one: lots of responsibility, very little bureaucracy, plenty to figure out, and a genuine chance to shape what this company becomes… and make a bunch of money as a result.
If that sounds exciting, LET'S PARTY.
Responsibilities:
- Architect, develop, and maintain backend components for our Risk Decisioning Platform.
- Build and orchestrate scalable backend services that automate, optimize, and monitor high-value credit and risk decisions in real time.
- Integrate with ORM layers - such as SQLAlchemy - and multi-RDBMS solutions (Postgres, MySQL, Oracle, MSSQL, etc. ) to ensure data integrity, scalability, and compliance.
- Collaborate closely with Product Team, Data Scientists, QA Teams to create extensible APIs, workflow automation, and AI governance features.
- Architect workflows for privacy, auditability, versioned traceability, and role-based access control, ensuring adherence to regulatory frameworks.
- Take ownership from requirements to deployment, seeing your code deliver real impact in the lives of customers and end users.
Requirements:
- Proficiency in Python, SQLAlchemy (or similar ORM), and SQL databases.
- Experience developing and maintaining scalable backend services, including API, data orchestration, ML workflows, and workflow automation.
- Solid understanding of data modeling, distributed systems, and backend architecture for regulated environments.
- Curiosity and drive to work at the intersection of AI/ML, fintech, and regulatory technology.
- Experience mentoring and guiding junior developers.
Technical Skills:
- Languages: Python 3.9+, SQL, JavaScript/TypeScript, Angular.
- Frameworks: Flask, SQLAlchemy, Celery, Marshmallow, Apache Spark.
- Databases: PostgreSQL, Oracle, SQL Server, Redis.
- Tools: pytest, Docker, Git, Nx.
- Cloud: Experience with AWS, Azure, or GCP preferred.
- Monitoring: Familiarity with OpenTelemetry and logging frameworks.
Senior AI Engineer
Company: Techjays
Experience: 4–8 Years
Location: Coimbatore, Hybrid
Joining: Immediate or within 30 days preferred
About the Role
We are looking for a Senior AI Engineer with strong Python development skills and hands-on experience building and deploying AI-powered applications. The ideal candidate should have practical knowledge of LLMs, Retrieval-Augmented Generation (RAG), vector databases, and scalable backend systems.
You will work closely with engineering and product teams to design, develop, and deploy reliable AI solutions for real-world business problems.
Key Responsibilities
- Design, develop, and maintain scalable backend applications using Python and frameworks such as Django, Flask, or FastAPI.
- Build and integrate AI-powered applications using LLMs, RAG pipelines, and agentic AI workflows.
- Develop document processing, embedding generation, semantic search, and retrieval pipelines.
- Integrate LLM APIs and optimize prompts, response quality, latency, and cost.
- Work with vector databases and relational databases to build efficient data retrieval systems.
- Design and implement REST APIs, asynchronous processing, caching, and queuing mechanisms.
- Apply software engineering best practices, including design patterns, clean code, testing, and version control.
- Deploy and maintain applications on AWS or GCP using Docker and CI/CD pipelines.
- Monitor production systems, troubleshoot issues, and improve application performance and reliability.
- Collaborate with cross-functional teams to translate business requirements into practical AI solutions.
- Contribute to code reviews, technical documentation, and knowledge sharing within the engineering team.
Required Skills
- 4–8 years of experience in software development, with strong hands-on Python expertise.
- Strong understanding of data structures, algorithms, object-oriented programming, and design patterns.
- Experience building backend applications using Django, Flask, or FastAPI.
- Hands-on experience with LLM-based applications and API integrations.
- Practical experience implementing RAG pipelines, embeddings, and semantic search.
- Experience with vector databases such as Pinecone, Qdrant, Weaviate, or Chroma.
- Strong knowledge of SQL and relational databases such as PostgreSQL or MySQL.
- Experience with caching, message queues, asynchronous processing, and WebSockets.
- Familiarity with AWS or GCP, Docker, Git, and CI/CD pipelines.
- Understanding of API design, system architecture, application security, and performance optimization.
- Experience testing, debugging, and maintaining production-grade applications.
Preferred Skills
- Experience building agentic AI applications and multi-agent workflows.
- Familiarity with LangChain, LangGraph, LlamaIndex, or similar frameworks.
- Knowledge of Model Context Protocol (MCP) and tool-calling mechanisms.
- Experience with LLM evaluation, hallucination reduction, and output quality monitoring.
- Familiarity with fine-tuning, model selection, and inference optimization.
- Experience with LLMOps, AI observability, and production monitoring.
- Knowledge of Kubernetes and microservices architecture.
What We’re Looking For
- Strong problem-solving and analytical skills.
- Ability to take ownership of features from development through deployment.
- Practical understanding of how to build reliable AI applications beyond prototypes.
- Ability to make sound technical decisions and explain architectural trade-offs.
- Good communication and collaboration skills.
- Willingness to learn, experiment, and work on challenging AI engineering problems.
Senior Technical Manager
Primary objective: Own engineering teams, architecture, delivery governance and successful execution of product and AI initiatives across DocTutorials.
Location
Hyderabad / Chennai
Employment
Full-time
Experience
10+ years
Role Summary
The Senior Technical Manager combines technical leadership, people management, product delivery and project execution. The role is accountable for team outcomes, engineering quality, timelines, production stability and the disciplined delivery of AI projects.
Key Responsibilities
1. Technology and Architecture Leadership
· Provide direction for Python FastAPI, React/Next.js, data, cloud and AI architectures.
· Review solution designs for security, scalability, maintainability, performance and cost.
· Define engineering standards and resolve complex cross-team technical risks.
· Remain technically hands-on through architecture reviews, critical code reviews and incident debugging.
2. People and Delivery Management
· Lead, mentor and develop engineering teams with clear goals and accountability.
· Own estimation, capacity, execution, dependencies, risks, releases and delivery recovery plans.
· Conduct regular one-to-ones, performance reviews, coaching and skill-development planning.
· Work with Product, QA, DevOps and stakeholders to deliver measurable product outcomes.
3. AI Project Execution
· Assess AI use cases for feasibility, data readiness, risk, cost and measurable value.
· Lead delivery of LLM, RAG, agentic and AI-assisted product initiatives from PoC to production.
· Ensure evaluation, human validation, security, privacy, observability and rollback controls.
· Prevent isolated demos, uncontrolled AI usage and dependency on individual engineers or vendors.
Required Skills and Experience
· 10+ years in software engineering with significant technical and people leadership experience.
· Strong understanding of Python/FastAPI, React/Next.js, APIs, databases, cloud and distributed systems.
· Proven ownership of product delivery, project planning, risk management and production operations.
· Experience hiring, mentoring, evaluating and developing engineering teams.
· Strong knowledge and execution experience across AI/ML, LLM, RAG or agentic-AI projects.
· Practical understanding of Generative AI, LLMs, RAG, Agentic AI and responsible AI use relevant to the role.
· Ability to use approved AI tools productively while protecting source code, credentials, learner data and organisational information.
· Commitment to human review, testing, security validation and traceability for AI-assisted outputs.
Good-to-Have Experience
· EdTech or medical-learning product experience.
· AWS, Kubernetes, DevSecOps, MLOps or LLMOps.
· Experience scaling teams and platforms through major transformation.
How Success Will Be Measured
· Delivery becomes predictable with risks identified early.
· Engineering quality, security and production stability improve.
· AI projects progress from validated use cases to reliable production outcomes.
· Team capability, ownership, engagement and succession strength increase.
· Work consistently delivers measurable outcomes and business value—not merely completion of assigned tasks or activities.
Expected mindset: Own the outcome, use AI responsibly, communicate risks early and deliver secure, measurable value for DocTutorials and its learners.
- We are seeking a high-velocity Senior Technical Lead with an overall experience
- of 12+ years in software engineering who thrives in an environment of autonomy
- and rapid iteration. At Nomiso, we don't just write code; we build resilient systems.
- This role is designed for a builder who embraces our core philosophy: Build, Ship,
- Measure, Improve. You will be responsible for taking features from a raw concept
- to a live environment, ensuring that every deployment delivers high technical
- excellence and system stability. You are not just an executor; you are a technical
- owner and system architect who understands that the "Ship" is only the midpoint of the system lifecycle.
What We’re Looking For (Who You Are)
● AI Systems Architect (5+ years in AI - LLM, RAG, Context Engineering, React, Prompt): You've shipped multiple production LLM systems at scale. Deep understanding of RAG, fine-tuning, prompt optimization, inference scaling, and cost management. You make pragmatic trade-offs between
accuracy, latency, and cost.You are accountable for the high quality solution and timely shipment of the feature as per committed timeline.
● Technical Lead Manager (TLM): In this role you will do 70% technical work and 30% people management & project management work. You've led engineering teams (4-8+ engineers). You grow engineers through mentoring, clear feedback, and ownership. You balance shipping speed with technical excellence and team development.
● The "Builder" Mentality: You have a bias toward action. You prefer a
working feature over a perfect specification and understand the value of
getting software into the hands of users early. You will not leave the tech
debt for a long time. Tech debt will be continuously addressed as product matures.
● Pragmatic Architect: You choose the right tool for the job, balancing
long-term scalability with the immediate need for speed and delivery.
● Cross-functional engagement: Partner with Product, QA, and Solution
Architects, Project manager to align execution with outcomes
● Continuous Learner: You view "Improvement" as a mandatory phase, not an optional one. You are eager to refactor and pivot based on objective evidence.
Requirement
AI Expertise
- LLM APIs (OpenAI, Anthropic, Hugging Face), model selection and trade-offs. RAG pipeline architecture, fine-tuning strategies, prompt engineering, Agentic patterns, multi-step reasoning, reliability under uncertainty
Fullstack depth
● Backend: Python (FastAPI,
Django) and Node.js (Express,
Nest.js)
● Frontend: React (TypeScript,
state management, performance
optimization)
● Databases: PostgreSQL (query
optimization, schema design,
scaling)
● Infrastructure: AWS (Lambda,
ECS, RDS, S3), Docker, CI/CD,
monitoring
Leadership
● Managed engineering teams
(4-8+ engineers)
Category Requirement
● Experience mentoring and
growing engineers
● Track record of building
high-performing teams
● Comfortable with ambiguity and
rapid decision-making
Experience 12+ years in a technical-focused
engineering environment.
Education Degree in CS or equivalent professional
experience.
You will operate within a cross-functional squad, collaborating daily with Solution
Architects and other engineering peers. You will ensure that features are released
safely and frequently, and own the success of the product, by analysing the
insights and user feedback. Our hierarchy is flat; you are expected to provide
technical leadership and mentorship to junior peers while having a direct line of
communication with leadership regarding technical strategy and technical debt.
Lead AI Engineer
Experience: 8+ Years
Location: Coimbatore / Hybrid
Joining: Immediate or within 30 days
About Techjays
At Techjays, we help businesses reimagine how they build, operate, and scale through AI. We focus on developing secure, scalable, production-grade AI solutions that solve real business problems and deliver measurable outcomes.
Our engineering team brings experience from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We combine strong engineering fundamentals with an execution-focused mindset to build advanced AI systems for global clients.
About the Role
We are looking for a Lead AI Engineer to drive the architecture and development of scalable backend systems and AI-powered applications.
In this role, you will lead the technical design and implementation of Python-based systems, oversee LLM integrations and RAG pipelines, and develop agentic AI workflows for production environments. You will take ownership of complex engineering challenges, establish coding and architectural standards, and mentor engineers to deliver reliable, maintainable, and high-performing solutions.
This is a hands-on technical leadership role for someone who can translate complex requirements into practical engineering solutions and take them from design to production.
Key Responsibilities
1. Backend Engineering & System Architecture
- Design and develop scalable, secure backend systems using Python and frameworks such as Django or Flask.
- Architect RESTful APIs, WebSocket services, and distributed systems that support high-performance applications.
- Apply design patterns, algorithms, and data structures to solve complex engineering challenges.
- Design efficient database schemas, caching strategies, and data access patterns for scalable applications.
- Establish engineering standards for code quality, testing, maintainability, and system performance.
2. AI Engineering & LLM Integration
- Architect and implement LLM-powered applications, retrieval-augmented generation (RAG) pipelines, and agentic AI workflows.
- Develop solutions using vector databases, embeddings, semantic search, and prompt engineering.
- Build and optimize multi-agent systems, orchestration workflows, and tool integrations using frameworks such as LangChain and LlamaIndex.
- Implement Model Context Protocol (MCP) integrations where appropriate to connect AI systems with external tools and data sources.
- Evaluate model fine-tuning approaches and other techniques to improve AI performance where required.
- Establish LLMOps practices covering evaluation, observability, quality monitoring, and cost and latency optimization.
3. Cloud Infrastructure & Deployment
- Design and deploy cloud-native applications using AWS and GCP services.
- Build and maintain CI/CD pipelines using Jenkins, GitLab CI, GitHub Actions, or similar tools.
- Containerize applications using Docker and support deployment and operations in Linux environments.
- Implement reliable asynchronous processing and messaging using queuing systems.
- Improve system availability, scalability, security, and deployment reliability across production environments.
4. Technical Leadership & Engineering Excellence
- Own technical decisions across complex backend and AI engineering initiatives.
- Guide engineers in architecture, implementation, debugging, code reviews, and engineering best practices.
- Identify performance bottlenecks and drive improvements in application reliability and scalability.
- Collaborate with product managers, frontend engineers, data scientists, and other stakeholders to deliver effective solutions.
- Evaluate emerging AI technologies, frameworks, and tools, adopting them when they provide meaningful technical or business value.
- Take ownership of features from technical design through implementation, deployment, and production support.
Required Technical Skills
Backend Development
- Strong Python programming expertise.
- Experience with Django, Flask, RESTful APIs, and WebSockets.
- Strong understanding of object-oriented programming, design patterns, algorithms, and data structures.
Databases & Performance
- Experience with PostgreSQL, MySQL, MongoDB, or equivalent database technologies.
- Strong understanding of relational database design, query optimization, and performance tuning.
- Experience implementing caching strategies and asynchronous processing.
Cloud & DevOps
- Hands-on experience with AWS and/or GCP.
- Experience with Git, Docker, Linux, and CI/CD pipelines.
- Familiarity with queuing systems and distributed application architectures.
System Design
- Ability to design secure, scalable, and maintainable backend systems.
- Experience making architecture decisions involving performance, reliability, scalability, and operational complexity.
Preferred AI/ML Skills
- Large Language Models (LLMs) and prompt engineering.
- Retrieval-Augmented Generation (RAG) architecture.
- Vector databases such as Pinecone, ChromaDB, or equivalent.
- Embeddings, semantic search, and retrieval optimization.
- Agentic AI workflows and multi-agent orchestration.
- Model Context Protocol (MCP) and tool integrations.
- LangChain, LlamaIndex, or similar frameworks.
- Model fine-tuning and LLMOps practices.
- AI evaluation frameworks, observability, and production quality monitoring.
- Experience optimizing inference costs, response latency, and AI application performance.
What We're Looking For
- Strong engineering fundamentals: You can solve complex technical problems and design maintainable systems.
- Hands-on ownership: You take responsibility for solutions from concept through production.
- System-level thinking: You understand how architecture, performance, security, and scalability work together.
- Practical AI expertise: You can build and deploy AI-powered applications beyond prototypes and proof of concepts.
- Technical leadership: You guide engineers, improve code quality, and establish sound engineering practices.
- Structured problem-solving: You make thoughtful technical decisions in ambiguous and fast-moving environments.
- Clear communication: You collaborate effectively across engineering and business teams.
- Continuous improvement: You stay current with evolving AI technologies and apply them where they create value.
What We Offer
- Competitive compensation.
- Flexible work environment with Coimbatore office and hybrid options.
- Paid holidays and flexible time off.
- Medical insurance for self and family, with coverage of up to ₹4 lakhs per person.
- Opportunities to architect and build production-grade AI systems used by real customers.
- Exposure to global clients and technically challenging projects.
- A culture that values ownership, clarity, integrity, and continuous learning.
Key Skills :
• Builds AI-powered business applications end to end, from the Python/FastAPI service layer through
to React-based user interfaces, deployed on Databricks
• Designs and builds APIs connecting AI agents, governed data and user-facing workflows, including
decision capture, audit logging and file exports for downstream systems
• Codes rule-based decision engines in Python (e.g. allocation or replenishment logic) that work
alongside ML models
• Integrates LLM agent runtimes into applications, including tool calls, streamed responses and cited
outputs
• Writes performant SQL against governed data and ensures services operate within defined access
boundaries
• Builds interactive screens, dashboards and conversational interfaces that let users review and act
on AI recommendations
• Works closely with GenAI/ML engineers, data engineers and BA
Only immediate joiners are considered.
Job Summary
We are looking for an experienced Python Developer with strong expertise in Generative AI (GenAI), Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG). The ideal candidate should have hands-on experience building and deploying AI-powered applications using Python, LangChain/LangGraph, and FastAPI.
Key Responsibilities
- Design, develop, and maintain scalable backend applications using Python.
- Build and implement Generative AI solutions using LLMs.
- Develop and optimize RAG-based applications and pipelines.
- Work with LangChain and LangGraph to build LLM-powered workflows and AI agents.
- Develop RESTful APIs and backend services using FastAPI.
- Integrate LLMs with enterprise applications, databases, and external services.
- Implement prompt engineering, context management, and response optimization.
- Work on vector databases and embedding models for semantic search.
- Ensure application scalability, performance, security, and reliability.
- Collaborate with cross-functional teams to deliver AI-driven solutions.
Mandatory Skills
- Strong hands-on experience in Python development.
- Practical experience with Generative AI and LLMs.
- Strong understanding and implementation experience of RAG architecture.
- Hands-on experience with LangChain and/or LangGraph.
- Experience developing REST APIs using FastAPI.
- Good understanding of LLM integration and prompt engineering.
Good to Have Skills
- Experience with OpenAI, Azure OpenAI, or other LLM providers.
- Knowledge of vector databases such as Pinecone, FAISS, Chroma, or Weaviate.
- Experience with embeddings and semantic search.
- Knowledge of Docker, Kubernetes, and cloud platforms (AWS/Azure).
- Exposure to AI agents and multi-agent systems.
- Experience with CI/CD and production deployment of AI applications.
This is a remote position.
About Leegality:
Leegality works with large Indian businesses to digitally transform critical compliance processes in a fast, easy and secure way.
We have multiple products across 2 categories:
Document Infrastructure:
Products that help businesses build paperless processes at scale:
- Document Execution Workflow: A unified platform for businesses to digitally execute (eSign, eStamp, Template Pre-fill, Document Fraud Prevention etc.) agreements, forms and other documents in a compliant way. Currently in use by 2000+ Indian businesses from giants like HDFC and SBI Cards to high-growth disruptors like goDigit and Cars24.
- Contract Management: An AI-powered platform for businesses to quickly review, negotiate and take action on contracts
- Signstation: A simple platform for businesses to digitally sign simple documents like invoices, policies and letters in a cost effective manner
Consent Infrastructure:
- Consentin: An end-to-end DPDP and Privacy compliance platform for Indian businesses
- Consentin Lens: A data discovery platform for businesses to identify the personal data they collect and store.
If you’re interested in building mission critical software that operates at population scale (75 million + Indians have signed at least one document through Leegality) then join Leegality.
Curious about our impact? Explore our customer success stories: leegality.com/case-studies
Our Culture
At Leegality, trust, ownership, transparency, and having fun while doing meaningful work are core to how we operate — not just values on paper. Our team rated us an incredible 97 eNPS for FY 2023–24 — the highest among 175+ startups surveyed.
We focus deeply on helping our people grow and stay motivated. Some of the perks you’ll enjoy:
- Flexible working hours
- Hybrid work setup
- Bi-annual performance appraisals
- A culture that rewards initiative, curiosity, and impact
If you're looking for a place where you can make a real difference while working with smart, driven, and genuinely nice people, welcome to Leegality.
Location: Hybrid
Role Overview
We are looking for a Technical Lead – Python to lead the design, development, and evolution of scalable backend systems that power Leegality's products. This role combines hands-on backend development with technical leadership, enabling you to influence architecture, mentor engineers, and drive engineering excellence across the team.
You will work closely with Product, Design, QA, DevOps, and other engineering teams to build reliable, secure, and high-performance applications while fostering a culture of ownership, collaboration, and continuous improvement.
Key Responsibilities
- Lead the design, development, and maintenance of scalable backend applications using Python.
- Own the technical architecture of backend systems, ensuring scalability, reliability, maintainability, and security.
- Design, develop, and optimize RESTful APIs and microservices for high-performance applications.
- Drive architectural decisions, establish engineering best practices, and promote clean, maintainable code.
- Conduct code reviews and mentor engineers through technical guidance, pair programming, and knowledge sharing.
- Lead technical estimation, sprint planning, solution design, and execution for engineering initiatives.
- Optimize application performance through database tuning, caching, asynchronous processing, and efficient system design.
- Ensure high code quality through unit testing, integration testing, CI/CD pipelines, and automated deployment practices.
- Troubleshoot and resolve complex production issues while driving root cause analysis and long-term improvements.
- Evaluate and adopt new technologies, frameworks, and engineering practices to continuously improve the platform.
- Build and foster a high-performing engineering culture focused on collaboration, accountability, innovation, and continuous learning.
Desired Skills
- 7–11 years of experience in backend software development, with at least 2–4 years in a technical leadership role.
- Strong proficiency in Python and object-oriented programming concepts.
- Hands-on experience with Python frameworks such as Django, Flask, or FastAPI.
- Strong understanding of RESTful API design and development, authentication mechanisms (JWT/OAuth), and API security best practices.
- Experience designing scalable backend architectures, distributed systems, and microservices.
- Strong knowledge of relational databases such as MySQL or PostgreSQL, with experience in query optimization, indexing, and schema design.
- Exposure to NoSQL databases such as MongoDB and caching technologies like Redis.
- Experience with cloud platforms such as AWS, containerization using Docker, orchestration using Kubernetes, and CI/CD pipelines.
- Strong understanding of software engineering best practices, including design patterns, SOLID principles, code reviews, testing, and documentation.
- Experience with version control systems such as Git and modern development workflows.
- Excellent analytical, problem-solving, communication, and stakeholder management skills.
- Ability to balance hands-on development with technical leadership and delivery ownership in a fast-paced product environment.
- Experience working in SaaS or product-based organizations is preferred.
- Exposure to AI-assisted development tools such as GitHub Copilot, Cursor, or ChatGPT is an added advantage.













