Senior Software Engineer

About the role

This role owns the design and delivery of Python-based backend systems that power Neuron7's AI-first service resolution platform. You will architect and implement customer-specific workflows that connect enterprise data and processes into reliable, scalable solutions. You own the full lifecycle of implementation features, from translating complex requirements into technical designs to deploying and maintaining production services. You will integrate AI and NLP capabilities into real-world service environments, ensuring that intelligent automation performs reliably at scale. You will act as a technical owner alongside customer success and solutions teams, guiding architecture decisions and ensuring alignment with client objectives. You will mentor junior engineers, contribute to internal tooling, and codify implementation patterns into reusable playbooks. Collaboration across engineering, ML, and customer-facing teams is central to how you will drive successful deployments and continuous improvement.

Key facts

What you'll do

Architect and develop Python-based backend services and APIs that form the core of customer implementations.

Build robust data ingestion, transformation, and validation pipelines to support AI and machine learning workflows.

Implement customer-specific business logic, connectors, and automations using Python microservices patterns.

Integrate internal ML pipelines, LLM components, and retrieval systems into production environments.

Work with RAG pipelines, embedding workflows, and NLP modules to enable intelligent resolution capabilities.

Collaborate closely with ML engineers to productionize models and optimize runtime performance and reliability.

Configure and deploy services across major cloud platforms including Azure, AWS, and GCP.

Ensure implementation services meet high standards of reliability, observability, and security.

Troubleshoot production incidents by analyzing logs, metrics, and traces to perform effective root-cause analysis.

Partner with Customer Success and Solutions teams to translate business requirements into precise technical specifications.

Own end-to-end technical implementation for enterprise accounts, ensuring timely and high-quality delivery.

Provide clear guidance on architecture best practices, scalable patterns, and integration strategies to internal teams.

Participate in rigorous code reviews to maintain code quality, consistency, and long-term maintainability.

Document implementation workflows, integration steps, and operational playbooks for future reuse.

Mentor junior team members and drive improvements to internal tooling and automation.

Requirements

Possess a total of 5+ years of professional software engineering experience.

Bring a minimum of 2+ years of hands-on Python coding experience to production systems.

Demonstrate a strong understanding of backend fundamentals, microservices architecture, and distributed systems principles.

Show proven experience working with APIs, web frameworks such as FastAPI, Flask, and Django, and RESTful architecture patterns.

Have hands-on experience with relational and NoSQL databases including PostgreSQL, MongoDB, or similar technologies.

Exhibit familiarity with major cloud platforms such as Azure, AWS, or GCP and their core services.

Apply strong problem-solving, debugging, and communication skills to complex technical challenges.

Collaborate effectively across cross-functional teams including engineering, machine learning, and customer-facing organizations.

Scope work, sequence delivery milestones, and proactively remove blockers that impact progress and quality.

Make informed trade-offs between scope, speed, and quality while adjusting plans to protect reliable delivery.

Contribute directly in the codebase when progress or clarity depends on implementation details.

Codify established working patterns into tools, playbooks, and building blocks that other engineers can leverage.

Ensure teams maintain momentum through clarity, thorough follow-through, and consistent execution.

Nice to have

Bring experience with AI, ML, and NLP pipelines including work with LLMs and RAG-based applications.

Demonstrate good knowledge of Java, advanced NLP or text processing techniques, or agentic implementation patterns.

Show familiarity with Docker, Kubernetes, and container orchestration in production environments.

Have exposure to message queues such as Kafka or RabbitMQ in distributed systems.

Experience with CI/CD tools and automation frameworks that support reliable deployments.

Have prior startup or scale-up experience working in fast-paced, growth-oriented environments.

Contribute to open-source projects or possess technical writing experience that demonstrates clear communication.

Practical notes

The role is based in Bangalore and offers a flexible hybrid working arrangement.

Neuron7 is an equal opportunity employer and values diversity, providing equal employment opportunities without discrimination or harassment.