PR - Manager

🤖 Data Scientist – Frontier AI for Data Platforms & Distributed Systems (4–8 Years)

Experience: 4–8 Years

Location: Bengaluru (On-site / Hybrid)

Company: Publicly Listed, Global Product Platform

🧠 About the Mission

We are building a Top 1% AI-Native Engineering & Data Organization — from first principles.

This is not incremental improvement.

This is a full-stack transformation of a large-scale enterprise into an AI-native data platform company.

We are re-architecting:

• Legacy systems → AI-native architectures
• Static pipelines → autonomous, self-healing systems
• Data platforms → intelligent, learning systems
• Software workflows → agentic execution layers

This is the kind of shift you would expect from companies like Google or Microsoft —

Except here, you will build it from day zero and scale it globally.

🧠 The Opportunity: This role sits at the intersection of three high-impact domains:

1. Frontier AI Systems: Large Language Models (LLMs), Small Language Models (SLMs), and Agentic AI

2. Data Platforms: Warehouses, Lakehouses, Streaming Systems, Query Engines

3. Distributed Systems: High-throughput, low-latency, multi-region infrastructure

We are building systems where:

• Data platforms optimize themselves using ML/LLMs
• Pipelines are autonomous, self-healing, and adaptive
• Queries are generated, optimized, and executed intelligently
• Infrastructure learns from usage and evolves continuously

This is: AI as the control plane for data infrastructure

🧩 What You’ll Work On

You will design and build AI-native systems deeply embedded inside data infrastructure.

1. AI-Native Data Platforms

• Build LLM-powered interfaces:
• Natural language → SQL / pipelines / transformations
• Design semantic data layers:
• Embeddings, vector search, knowledge graphs
• Develop AI copilots:
• For data engineers, analysts, and platform users

2. Autonomous Data Pipelines

• Build self-healing ETL/ELT systems using AI agents
• Create pipelines that:
• Detect anomalies in real time
• Automatically debug failures
• Dynamically optimize transformations

3. Intelligent Query & Compute Optimization

• Apply ML/LLMs to:
• Query planning and execution
• Cost-based optimization using learned models
• Workload prediction and scheduling
• Build systems that:
• Learn from query patterns
• Continuously improve performance and cost efficiency

4. Distributed Data + AI Infrastructure

• Architect systems operating at:
• Billions of events per day
• Petabyte-scale data
• Work with:
• Distributed compute engines (Spark / Flink / Ray class systems)
• Streaming systems (Kafka-class infra)
• Vector databases and hybrid retrieval systems

5. Learning Systems & Feedback Loops

• Build closed-loop AI systems:
• Execution → feedback → model updates
• Develop:
• Continual learning pipelines
• Online learning systems for infra optimization
• Experimentation frameworks (A/B, bandits, eval pipelines)

6. LLM & Agentic Systems (Infra-Aware)

• Build agents that understand data systems
• Enable:
• Autonomous pipeline debugging
• Root cause analysis for infra failures
• Intelligent orchestration of data workflows

🧠 What We’re Looking For

Core Foundations

• Strong grounding in:
• Machine Learning, Deep Learning, NLP
• Statistics, optimization, probabilistic systems
• Distributed systems fundamentals
• Deep understanding of:
• Transformer architectures
• Modern LLM ecosystems

Hands-On Expertise

• Experience building:
• LLM / GenAI systems (RAG, fine-tuning, embeddings)
• Data platforms (warehouse, lake, lakehouse architectures)
• Distributed pipelines and compute systems
• Strong programming skills:
• Python (ML/AI stack)
• SQL (deep understanding — query planning, optimization mindset)

Systems Thinking (Critical)

You think in systems, not components.

• Built or worked on:
• Large-scale data pipelines
• High-throughput distributed systems
• Low-latency, high-concurrency architectures
• Understand:
• Query optimization and execution
• Data partitioning, indexing, caching
• Trade-offs in distributed systems

🔥 What Sets You Apart (Top 1%)

• Built AI-powered data platforms or infra systems in production
• Designed or contributed to:
• Query engines / optimizers
• Data observability / lineage systems
• AI-driven infra or AIOps platforms
• Experience with:
• Multi-modal AI (logs, metrics, traces, text)
• Agentic AI systems
• Autonomous infrastructure
• Worked on systems at scale comparable to:
• Google (BigQuery-like systems)
• Meta (real-time analytics infra)
• Snowflake / Databricks (lakehouse architectures)

🧬 Ideal Background (Not Mandatory)

We often see strong candidates from:

• Data infrastructure or platform engineering teams
• AI-first startups or research-driven environments
• High-scale product companies

Experience building:

• Internal platforms used by 1000s of engineers
• Systems serving millions of users / high throughput workloads
• Multi-region, distributed cloud systems

🧠 The Kind of Problems You’ll Solve

• Can LLMs replace traditional query optimizers?
• How do we build self-healing data pipelines at scale?
• Can data systems learn from every query and improve automatically?
• How do we embed reasoning and planning into infrastructure layers?
• What does a fully autonomous data platform look like?

Background: We Commonly See (But Not Limited To)

Our team often includes engineers from top-tier institutions and strong research or product backgrounds, including:

• Leading engineering schools in India and globally
• Engineers with experience in top product companies, AI startups, or research-driven environments
• That said, we care far more about demonstrated ability, depth, and impact than pedigree alone.

1. Develop and maintain server-side logic and APIs using Node.js.
2. Collaborate with front-end developers to integrate user-facing elements with server-side logic.
3. Design and implement scalable, secure, and maintainable backend solutions.
4. Work with databases such as MongoDB, PostgreSQL, or MySQL.
5. Optimize application performance and troubleshoot production issues.
6. Follow best practices for testing, deployment, and code quality.
7. Stay updated with the latest trends and technologies in backend

• Hands-on expertise in managing technical teams and work closely with business stakeholders
• Should be familiar with card testing and POS ecosystem.
• Experience with designing APIs and building platform integrations in Commerce, POS, FinTech and Payments
• Payment’s domain experience.
• Extensive experience on Base24 & SWITCH part for payment format.
• Exposure on ISO8583 Messaging system.
• API understanding and creation.
• Working knowledge on cryptographic algorithms (RSA, EC, AES, SHA variants), TLS/SSL protocols. C Symetric and A symetrics, K.M.S.
• Digital Payments technical knowledge - QR/ POS/ UPI/ BQR
• Understanding of CI/CD pipelines, Kubernetes, containerization, Docker
• Must have strong technical skills in Android APK and iOS development Concept and Web services.
• Supportability, monitoring, ops in general.
• Accurate cost models to deploy and operate
• Extensive experience in TLOG’s, data integration with downstream applications, and impact of POS changes on different financial, legal, compliance, loss prevention, etc. applications.
• Extensive experience with payment systems 7861 (EMV, payment middleware, encryption, tokenization, settlement, offline scenarios,).
• Extensive experience with different types of payment methods including credit, debit, gift cards (Both closed loop and open loop), PLCC, PayPal, AliPay, checks, etc. as well as different payment form factors like Tap N Go, contactless, swipe, EMV, Mobile, etc.
• Extensive experience with payment devices (pin pads, printers, registers, scanners).
• Experience in Node.js / Java / Python, building REST APIs, with experience/exposure to front end stack like JavaScript & React / Angular. 
• Experience with Storage systems - RDBMS, NoSQL (Cassandra/MongoDB), Redis/Memcache/Aerospike.
• Experience in messaging tools like Kafka/AWS Kinesis etc...
• Design expertise for performance, scalability, fault tolerance and high availability

• Experience with POS systems and Payments domain.
• Demonstrated experience for systems architecture, design, and integration for POS systems
• Java and/or Node.js. Experience building micro services (REST APIs) using Node.js
• Experience with one or more RDBMS databases like MySql, PostGreSQL
• Experience with one or more NoSQL databses like MongoDB, Cassandra, DynamoDB, Aerospike, Elastic Search, Redis, neo4j etc.,
• Caching technologies like: Redis, Elasticache,
• Cloud Providers like: AWS/ Google Cloud / Azure
• CI / CD : Jenkins, Docker, Kubernete
  

Job Description:
We are looking for a Software Engineer with solid development experience in Java and related frameworks. We are looking for a self-motivated, go-getter, out-of-the-box thinker who is ready to work in a high-energy start-up environment. He/she must demonstrate a high level of ownership, integrity, and creativity.
Required Skills:
• Core Java (Proficient)
• Spring, Spring MVC OR Spring boot
• Hibernate – Good to have
• Oracle/MySQL DB - Hands-on (Intermediate)
• REST API and AWS– Good to have
• Hands-on experience of working on Spring boot based Microservices (Intermediate)
• Good to have knowledge of Microservice DevOps tools (Git, Jenkins, JUnits, deployment, monitoring, tracing)
• Sound understanding of core Java, SOAP Services, REST Services, Spring & maven, having expertized to work on Unix platform
• Should have working knowledge on web servers (e.g. Apache HTTP) and application servers (e.g. Tomcat, WebLogic)
• Should have a working knowledge of any relational database. Preferred will be Oracle and MySQL.
Roles and Responsibilities:
• You will design, develop, modify, debug and/or maintain software code according to functional, non-functional and technical design specifications.
• You will follow software engineering standards, applicable software development
methodology and release processes, to ensure code is maintainable, scalable,
supportable and demo the software products to stakeholders
• You will investigate issues by reviewing/debugging code, providing fixes and workarounds, and reviewing changes for operability to maintain existing software solutions.
• You will work within a team, collaborate and add value through participation in peer code reviews, provide comments and suggestions, work with cross-functional teams to achieve goals.

Why should you join Opcito?
We are a dynamic company that believes in designing transformation solutions for our customers with our ability to unify quality, reliability, and cost-effectiveness at any scale. Our core work culture focuses on adding material value to client products by leveraging best practices in DevOps like continuous integration, continuous delivery, and automation, coupled with disruptive technologies like cloud, containers, serverless computing, and microservice-based architectures.
Here are some of the perks of working with Opcito:
• Outstanding career development and learning opportunities
• Competitive compensation depending on experience and skill
• Friendly team and enjoyable work environment
• Flexible working schedule
• Corporate and social events.

•SaaS platform, and from a marketing background preferable.

• Conducting market research to identify selling possibilities and evaluate customer needs.

• Actively seeking out new sales opportunities through calling, networking and social media.

• Designing and implementing marketing plans for the company products.

• Answering to client queries about product specifications and uses.

• Develop relationships with existing customers and keeping touch with them.

• Work with other team members to ensure customer satisfaction.

• Find new business opportunities and customers.

• Contact potential customers to showcase company products or services.

• Use of social media like LinkedIn, after connecting to customers dropping emails like an introductory template or a pdf, scheduling demos and sending proposals and sales.

 •Preferred: Females

• To appoint Block Sales Manager in their respective Districts.
• To manage sales operations in assigned district to achieve revenue goals.
• To supervise sales team members on daily basis and provide guidance whenever needed.
• To identify skill gaps and conduct trainings to sales team.