Python Developer

Role & Responsibilities

As a Senior GenAI Engineer you will own the AI layer of our product — building the features that make Zenskar intelligent. This is not a research role and not a prompt-engineering role. You will build production AI systems that enterprise clients depend on, which means reliability, observability, and rigorous evals matter as much as the AI capability itself. You own the full vertical — the model, the pipeline, and the UI.

• Build and own CS Copilot — a real-time assistant for customer success teams, spanning STT pipelines, live transcription, and LLM-powered suggestions
• Build LLM-powered document understanding features — extracting structured, reliable data from unstructured enterprise documents
• Own AI feature UIs end-to-end — you build the interface, not just the model integration layer
• Design and maintain an eval framework — define what 'working' means for each AI feature and catch regressions before users do
• Drive model selection and integration decisions — choosing the right provider and approach for each use case, managing latency and cost
• Own AI platform reliability — observability, fallback behaviour, and graceful degradation when models fail
• Work closely with product, customer success, and the full-stack engineer — AI features only matter if they are usable and trusted by real users

THE IMPACT YOU'LL MAKE-

• You will define what AI means at Zenskar — the features you ship will be the most visible and differentiated parts of the product
• CS Copilot, if done well, changes how enterprise customer success teams operate every single day — this is a high-stakes, high-visibility surface
• You will establish the engineering culture around AI reliability at Zenskar — evals, observability, and disciplined iteration
• Your work will directly accelerate enterprise deals — AI features are increasingly a buying criterion for our clients
• You will be the person who brings engineering rigour to a domain where most companies ship demos and call it a feature

Ideal Candidate

• Strong Senior GenAI / AI Backend Engineer Profiles
• Mandatory (Experience 1) – Must have 4+ years of total software development experience, with at least 2+ years working on AI/LLM-based features in production
• Mandatory (Experience 2) – Must have strong backend engineering experience using Python (FastAPI / Django preferred) and building production-grade systems
• Mandatory (Experience 3) – Must have hands-on experience building LLM-based applications, including OpenAI / Gemini / similar models in real projects
• Mandatory (Experience 4) – Must have experience with RAG (Retrieval Augmented Generation) including chunking, embeddings, and retrieval pipelines
• Mandatory (Experience 5) – Must have experience designing end-to-end AI pipelines, including chaining, tool usage, structured outputs, and handling failure cases
• Mandatory (Experience 6) – Must have experience building agentic AI systems (multi-step workflows, tool orchestration like LangGraph / CrewAI or custom agents)
• Mandatory (Experience 7) – Must have strong coding and system design skills, not just prompt engineering or experimentation
• Mandatory (Experience 8) – Must have experience shipping AI features in production, not just POCs or research projects
• Mandatory (Experience 9) – Must have experience working with APIs, backend services, and integrations
• Mandatory (Experience 10) – Must have understanding of AI system reliability, including latency, cost optimization, fallback handling, and basic eval thinking
• Mandatory (Company) – Product companies / startups, preferably Series A to Series D
• Mandatory (Note) - Candidate's overall experience should not be more than 7 Yrs
• Mandatory (Tech Stack) – Strong in Python + AI/LLM ecosystem, experience with modern AI tooling and frameworks
• Mandatory (Exclusion) – Reject profiles that are only Prompt Engineers, Data Scientists, or Frontend Engineers without strong backend + system building experience
• Preferred (Skill) – Experience with fine-tuning (LoRA / QLoRA) or open-source model deployment (vLLM / Ollama)
• Preferred (Frontend) – Basic ability to build or contribute to frontend (React or similar)
• Highly Preferred (Education) – Candidates from Tier-1 institutes (IITs, BITS, NITs, IIITs, top global universities)

As a Python Engineer, you will play a critical role in building and scaling data pipelines, developing prompts for large language models (LLMs), and deploying them as efficient, scalable APIs. You will collaborate closely with data scientists, product managers, and other engineers to ensure seamless integration of data solutions and LLM functionalities. This role requires expertise in Python, API design, data engineering tools, and a strong understanding of LLMs and their applications.

• Back-end software development
• Software engineering and designing data models and write effective APIs
• Working together with engineers and product teams
• Understanding business use cases and requirements for different internal teams
• Maintenance of existing projects and New feature development
• Consume and integrate classifier/ ML snippets from Data science team

What we are looking for:

• 4+ years of industry experience with the Python and Django framework.
• Degree in Computer Science or related field
• Good analytical skills with strong fundamentals of data structures and algorithms
• Experience building backend services with hands-on experience through all stages of Agile software development life cycle.
• Ability to write optimized codes,debug programs, and integrate applications with third party tools by developing various APIs
• Experience with Databases (Relational and Non-Relational). Ex: Cassandra, MongoDB, Postgresql
• Experience with writing REST-APIs.
• Prototyping initial collection and leveraging existing tools and/or creating new tools
• Experience working different types of datasets (e.g. unstructured, semi-structured, with missing information)
• Ability to think critically and creatively in a dynamic environment, while picking up new tools and domain knowledge along the way
• A positive attitude, and a growth mindset

Bonus:

• Experience with relevant Python libraries such as Sklearn, NLTK, tensorflow, HuggingFace Transformers
• Hands on experience in Machine learning implementations
• Experience with Cloud infrastructure (e.g. AWS) and relevant microservices
• Good with Humor and Team player

• Expert in Python, with knowledge of Python web framework Django
• Familiarity with some ORM (Object Relational Mapper) libraries
• Able to integrate multiple data sources and databases into one system
• Basic understanding of front-end technologies, such as JavaScript, HTML5 and CSS3
• Familiarity with event-driven programming in Python
• Strong experience on Linux
• Solid database skills in a relational database (i. e. PostgresSQL)
• Able to create database schemas that represent and support business processes
• Strong unit test and debugging skills
• Proficient understanding of code versioning tools (git)
• Experience on RESTful APIs
• Experience deploying on AWS is desirable
• Experience on Automation Builds using Jenkins and other popular frameworks
• Strong analytical and problem-solving skills paired with the ability to develop creative and efficient solutions
• Excellent interpersonal, leadership, influence and communication skills
• Experience in designing scalable micro-services is desirable

Our goal

We are reinventing the future of MLOps. Censius Observability platform enables businesses to gain greater visibility into how their AI makes decisions to understand it better. We enable explanations of predictions, continuous monitoring of drifts, and assessing fairness in the real world. (TLDR — build the best ML monitoring tool)

The culture

We believe in constantly iterating and improving our team culture, just like our product. We have found a good balance between async and sync work — default is still Notion docs over meetings, but at the same time, we recognize that as an early-stage startup brainstorming together over calls leads to results faster. If you enjoy taking ownership, moving quickly, and writing docs, you will fit right in.

The role:

Our engineering team is growing and we are looking to bring on board a senior software engineer who can help us transition to the next phase of the company. As we roll out our platform to customers, you will be pivotal in refining our system architecture, ensuring the various tech stacks play well with each other, and smoothening the DevOps process.

On the platform, we use Python (ML-related jobs), Golang (core infrastructure), and NodeJS (user-facing). The platform is 100% cloud-native and we use Envoy as a proxy (eventually will lead to service-mesh architecture).

By joining our team, you will get the exposure to working across a swath of modern technologies while building an enterprise-grade ML platform in the most promising area.

Responsibilities

• Be the bridge between engineering and product teams. Understand long-term product roadmap and architect a system design that will scale with our plans.
• Take ownership of converting product insights into detailed engineering requirements. Break these down into smaller tasks and work with the team to plan and execute sprints.
• Author high-quality, highly-performance, and unit-tested code running on a distributed environment using containers.
• Continually evaluate and improve DevOps processes for a cloud-native codebase.
• Review PRs, mentor others and proactively take initiatives to improve our team's shipping velocity.
• Leverage your industry experience to champion engineering best practices within the organization.

Qualifications

Work Experience

• 5+ years of industry experience (3+ years in a senior engineering role) preferably with some exposure in leading remote development teams in the past.
• Proven track record building large-scale, high-throughput, low-latency production systems with at least 3+ years working with customers, architecting solutions, and delivering end-to-end products.
• Fluency in writing production-grade Go or Python in a microservice architecture with containers/VMs for over 5+ years.
• 2+ years of DevOps experience (Kubernetes, Docker, Helm and public cloud APIs)
• Worked with relational (SQL) as well as non-relational databases (Mongo or Couch) in a production environment.
• (Bonus: worked with big data in data lakes/warehouses).
• (Bonus: built an end-to-end ML pipeline)

Skills

• Strong documentation skills. As a remote team, we heavily rely on elaborate documentation for everything we are working on.
• Ability to motivate, mentor, and lead others (we have a flat team structure, but the team would rely upon you to make important decisions)
• Strong independent contributor as well as a team player.
• Working knowledge of ML and familiarity with concepts of MLOps

Benefits

• Competitive Salary 💸
• Work Remotely 🌎
• Health insurance 🏥
• Unlimited Time Off ⏰
• Support for continual learning (free books and online courses) 📚
• Reimbursement for streaming services (think Netflix) 🎥
• Reimbursement for gym or physical activity of your choice 🏋🏽‍♀️
• Flex hours 💪
• Leveling Up Opportunities 🌱

You will excel in this role if

• You have a product mindset. You understand, care about, and can relate to our customers.
• You take ownership, collaborate, and follow through to the very end.
• You love solving difficult problems, stand your ground, and get what you want from engineers.
• Resonate with our core values of innovation, curiosity, accountability, trust, fun, and social good.