Principle Engineer Backend

Design, develop, and maintain backend services using Java

Build scalable RESTful APIs and microservices

Work with Spring / Spring Boot frameworks

Implement business logic, data access layers, and integrations

Optimize application performance, scalability, and security

Write clean, testable, and maintainable code

Perform unit and integration testing

Participate in code reviews and technical discussions

Collaborate with frontend, DevOps, and QA teams

Troubleshoot and resolve produc

Application Deployment Engineers / Deployment Engineer – Video Analytics / CCTV Solutions / Application Implementation Engineer

Company Name

Paralaxiom Technologies Private Limited

Company Website

https://www.vast.vision/

https://www.linkedin.com/company/paralaxiom

Company details

Paralaxiom Technologies is involved in deep learning algorithms to develop video analytics-based security and compliance applications. They offer OCR products and image classification tools enhanced by machine learning algorithms and robust statistical analysis. We are among the earliest practitioners of AI software and we have world-class credentials in these technologies. They offer products like Paralaxiom VAST(Video Analytics and Surveillance Toolkit) and Paralaxiom AMPLE(Paralaxiom natural language processing platform).

In today's world, all premises be it manufacturing, hospitals, offices, hotels, cities, airports, shops, warehouses etc. are covered with CCTV Cameras. Continuous monitoring through dedicated command center or e-surveillance is proving to be ineffective as well as costly to manage.

We have pioneered the use of AI / ML technologies to headlessly live monitor CCTV cameras to generate very accurate alerts, alarms & insights and deliver them directly to the right stakeholders for quick, proactive action.

We have worked closely with hundreds of customers from diverse industries, AI Hardware Partners, CCTV OEMs, VMSs, System Integrators & Consultants to bring to the world VAST, an enterprise-ready Video Surveillance as a Service (VSaaS) solution.

Location: Pune / Bangalore / Chennai

Mode of Working: Work From Office 

Days of Working: 5 Days a week

Responsibilities

Position Overview:

Paralaxiom is a video analytics and machine vision company with its VAST product line a path-breaking product for safety, security, and operations for CCTV operations.

We are looking for application engineers for this product line.

Experience: 1 -2 years

Key Responsibilities:

1) Gathering information from customers on their needs and understanding how VAST software matches their desires

2) Design the solution and installation of the software

3 ) Making sure the VAST software continues to work properly after maintenance and testing

4) Take notes of all aspects of the application for future upgrades and maintenance

5) Troubleshooting the software

6) Training the end users

7) Excellent Knowledge of Python and shell scripting

8) Working knowledge of IP networking and troubleshooting

We need someone with 1-2 years of experience with the following skillset:

Great communication skills

Debugging and analytical skills

Knowledge of hardware and software integration will be a plus

Knowledge of Camera NVR will be a plus

Hands-on system and functional testing will be a plus

Interview process: 3 Video + Final Discussion - F2F

Founding Engineer (Bangalore)

The problem:

Business enterprises overpay vendors - on every batch of invoices, on every month because the data that would catch lives in different systems. We are building an AI agent that processes invoices end-to-end, reasons across all the relevant sources, flags genuine discrepancies, and acts - without a human having to investigate each one.

What you will own

Everything engineering. Schema design to deployment to the 2am fix when something breaks in production. There is no tech lead above you. There is no platform team. There is the architecture, you, and the founders. Concretely, this means building:

• A multi-stage agentic pipeline that takes a vendor invoice and produces a structured decision - fully autonomous for clear cases, escalating to human review for genuinely ambiguous ones. We use LangGraph, but if you've built equivalent systems with Temporal, Prefect, or custom state machines with LLM orchestration, that works
• An LLM-powered extraction layer that handles real invoices - scanned PDFs, stamped documents, inconsistent layouts - and returns structured output
• A graph data model that connects invoices to various sources and can traverse those relationships to detect discrepancies
• ERP connectors, GST validation logic, and a write-back layer that closes the loop

What we need

• Strong Python. Async FastAPI, clean service boundaries, tests that actually catch bugs. You have shipped Python backends that handled real production load
• Solid Postgres. Complex queries, schema design, migrations without downtime, row-level security for multi-tenant data. pgvector is a plus - if not, you pick it up fast
• LLM API experience in production. You have called an LLM API for something that real users depended on. You know about structured output, retry logic, cost management, prompt versioning. A side project counts if it was genuinely deployed
• Comfort with graph data models. You understand when a graph is the right structure and when it is not. You do not need deep Neo4j production experience - you need to understand graph relationships conceptually and be willing to learn Cypher. It is a 2-day ramp for the right person
• Working knowledge of deployment. Deployed and operated production workloads on GCP. Cloud Run, Cloud SQL, Cloud Storage, Redis — you're comfortable across the stack. If you've done it on AWS, the translation isn't hard, but GCP is where we are
• You own things. Not "I contributed to" - you designed it, shipped it, and fixed it when it broke. That pattern needs to be visible in your history

Good to have, not mandatory

• Built an agentic pipeline with multiple stages
• Any fintech, P2P domain experience - even tangential
• Worked at a startup with under 20 people
• Has a GitHub, blog, or writeup that shows how you think about a hard technical problem

What you get

• The hardest engineering problem you would have worked on. This is not CRUD with an LLM bolted on
• Real ownership. First engineering hire. Your architectural decisions will be in this product five years from now
• Equity that matters. ESOP - Open to discussion. We are pre-seed - this is a bet, not a guarantee. We will not pretend otherwise
• No meetings tax. You work directly with the founders. The product is specified clearly. You know what you are building and why

Honest about stage: We do not have a production ready infra yet. We have a complete architecture specification and a working prototype. If you need the stability of an established engineering org, this is not the right moment. If you want to build something real from zero and own a meaningful piece of it, it is.

The founders

One of us has spent 20 years building revenue and operational engines at companies where there was no playbook - part of the pilot team that established the world's largest search company's direct sales operations in India, managed global operations for a global mobile advertising platform, scaled a B2C platform to become one of India’s leading edtech platforms and most recently worked on building an enterprise Agentic Voice AI platform. The other has spent 15 years taking AI from demo to production in domains where failure is expensive - voice, lending, and conversational systems across a Series D conversational AI company, a major telco, a Big 4, and a leading NBFC.

Two IIT/IIM alumni who have both watched AI work in enterprise, and know exactly what it takes to get it there. We are not building this product because it sounds interesting. We are building it because we have both sat across the table from CFOs who know they are losing margin and have no tool capable of doing anything about it.

Data Platform engineering at Uber is looking for a strong Technical Lead (Level 5a Engineer) who has built high quality platforms and services that can operate at scale. 5a Engineer at Uber exhibits following qualities: 

• Demonstrate tech expertise › Demonstrate technical skills to go very deep or broad in solving classes of problems or creating broadly leverageable solutions. 
• Execute large scale projects › Define, plan and execute complex and impactful projects. You communicate the vision to peers and stakeholders.
• Collaborate across teams › Domain resource to engineers outside your team and help them leverage the right solutions. Facilitate technical discussions and drive to a consensus.
• Coach engineers › Coach and mentor less experienced engineers and deeply invest in their learning and success. You give and solicit feedback, both positive and negative, to others you work with to help improve the entire team.
• Tech leadership › Lead the effort to define the best practices in your immediate team, and help the broader organization establish better technical or business processes.

What You’ll Do

• Build a scalable, reliable, operable and performant data analytics platform for Uber’s engineers, data scientists, products and operations teams.
• Work alongside the pioneers of big data systems such as Hive, Yarn, Spark, Presto, Kafka, Flink to build out a highly reliable, performant, easy to use software system for Uber’s planet scale of data. 
• Become proficient of multi-tenancy, resource isolation, abuse prevention, self-serve debuggability aspects of a high performant, large scale, service while building these capabilities for Uber's engineers and operation folks.

What You’ll Need

• 7+ years experience in building large scale products, distributed systems in a high caliber environment.
• Architecture: Identify and solve major architectural problems by going deep in your field or broad across different teams. Extend, improve, or, when needed, build solutions to address architectural gaps or technical debt.
• Software Engineering/Programming: Create frameworks and abstractions that are reliable and reusable. advanced knowledge of at least one programming language, and are happy to learn more. Our core languages are Java, Python, Go, and Scala.
• Platform Engineering: Solid understanding of distributed systems and operating systems fundamentals such as concurrency, multithreading, file systems, locking etc.
• Execution & Results: You tackle large technical projects/problems that are not clearly defined. You anticipate roadblocks and have strategies to de-risk timelines. You orchestrate work that spans multiple teams and keep your stakeholders informed.
• A team player: You believe that you can achieve more on a team that the whole is greater than the sum of its parts. You rely on others’ candid feedback for continuous improvement.
• Business acumen: You understand requirements beyond the written word. Whether you’re working on an API used by other developers, an internal tool consumed by our operation teams, or a feature used by millions of customers, your attention to details leads to a delightful user experience.