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🤖 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.

Job Title: Data Architect – AI/ML (Travel Domain)

We’re hiring a Data Architect to build and scale data systems powering AI/ML solutions in the travel domain. In this role, you will design data lakes/warehouses, create robust ETL pipelines, and enable real-time analytics for flight, hotel, and booking platforms. You will work closely with data scientists and engineering teams to support personalization, pricing, and recommendation engines.

Key Requirements:

• 5+ years in data architecture / engineering
• Strong experience with AWS/GCP/Azure and big data tools
• Expertise in ETL, data modeling, and pipeline design
• Good understanding of ML data workflows
• Experience in travel, e-commerce, or high-volume platforms is a plus

If you’re passionate about building scalable data ecosystems and driving AI-led innovation, we’d love to connect.

Job Title: Head of Human Resources

Location: [Specify Location]

CTC: ₹60–70 Lakhs per annum

Reporting To: CEO / Managing Director

Role Overview

The Head of Human Resources will lead the organization’s HR strategy, driving talent acquisition, performance management, leadership development, employee engagement, and compliance. This role requires a strategic HR leader with strong business acumen and the ability to align people initiatives with organizational goals.

Key Responsibilities

Strategic HR Leadership

Develop and implement HR strategies aligned with business objectives.

Partner with leadership to support organizational growth and transformation.

Drive workforce planning and succession management.

Talent Acquisition & Employer Branding

Oversee recruitment for leadership and critical roles.

Strengthen employer branding and talent pipelines.

Performance & Talent Management

Design and manage performance management systems.

Lead leadership development and high-potential programs.

Drive learning and development initiatives.

Compensation & Benefits

Design competitive compensation structures and incentive plans.

Ensure internal equity and market alignment.

Employee Engagement & Culture

Promote a high-performance, inclusive work culture.

Lead employee engagement, retention, and wellness programs.

HR Operations & Compliance

Ensure compliance with labor laws and statutory requirements.

Oversee HR policies, audits, and governance frameworks.

Change Management

Lead HR initiatives during organizational change, M&A, or expansion.

Required Qualifications

MBA / PGDM in HR or equivalent.

15–20+ years of progressive HR leadership experience.

Prior experience as Head of HR / HR Director in a mid-to-large organization.

Strong knowledge of Indian labor laws and HR best practices.

Proven experience in strategic HR transformation.

Key Skills & Competencies

Strategic thinking & business partnering

Leadership & stakeholder management

Talent management & succession planning

Compensation strategy

Change management

Look for someone who has worked on Manufacturing Industry,stability,5 working days.

Position: Trainee Electronics Engineer

Location: Gandhinagar, Gujarat

Employment Type: Full-time, On-site

Experience: 6 month to 2 year (Freshers Preferred)

Salary: ₹19,000 CTC (Starting)

Key Responsibilities

• Assist in testing, troubleshooting, and maintenance of electronic equipment and systems.
• Understand and interpret electrical and electronic circuit drawings.
• Perform on-site service and support activities as required.
• Work closely with senior engineers to learn and implement engineering best practices.
• Prepare and maintain technical documentation and service reports.

Required Skills & Qualifications

• Qualification: B.E. in Electronics Engineering.
• Strong understanding of basic electronics concepts, measuring units, instruments, and electrical properties of components.
• Ability to read and interpret electrical drawings.
• Good communication skills – must be able to read, write, and speak in English.
• Willingness to travel for service and field assignments.
• Freshers and local candidates will be given preference.

Insurity’s Next Software Engineer II

We are seeking an experienced and highly capable Software Engineer II to join our Bridge product team. This role offers the opportunity to shape the future of a core Insurity platform by building new features, modernizing both frontend and backend components, and improving system performance. The ideal candidate will bring strong technical depth, collaborative instincts, and an automation mindset—along with a passion for using next-generation tooling to enhance delivery. You’ll play a key role in projects that include UI/API modernization, system integrations, and performance tuning, while also helping to adopt agentic workflows and internal automations that scale team impact.

What Our Software Engineer II Will Do

• Design, build, and ship features across a large .NET microservices suite; own your code from design through production.
• Own quality as part of engineering: write and maintain the automation needed to protect your services (unit, integration, contract, and targeted e2e). “Done” = coded, reviewed, tested, observable, deployed.
• Evolve APIs (REST/JSON; some SOAP): define clear contracts, enforce backward-compatibility with contract tests.
• Level up automation & CI/CD: improve pipelines, quality gates, coverage, and deployment reliability; reduce flaky tests and speed feedback loops.
• Operate what you build: add logs/metrics/traces, triage issues, root-cause and fix defects.
• Partner with QA on test strategy for your changes; QA is a collaborator, not a handoff.
• Lean into generative AI to go faster—safely:
• Use coding assistants (e.g., Copilot/ChatGPT/Replit) to draft code/tests/docs and verify outputs.
• Generate synthetic test data/cases from API contracts; summarize PRs, changelogs, and incidents.
• Build lightweight internal automations (e.g., PR reviewers, log triage helpers) under our governance.
• Document decisions and how to test/use your services.

     Within 6–18 months you will:

• Independently deliver simple → moderately complex enhancements end-to-end with solid estimates.
• Extend shared test/utilities as needed for your services (you’re not a test-framework team).
• Write concise technical docs for engineers, QA, support, and ops.

Who We’re Looking For

• 6–10 years building and shipping production services/features.
• C#/.NET (ASP.NET Core, Web API), SQL Server; microservices fundamentals (service boundaries, resiliency, observability).
• Quality-through-code (must-have): you routinely add unit/integration/contract tests for the code you ship; comfortable with Playwright/Cypress or Postman/Newman for targeted e2e; GitHub Actions/Azure DevOps/Jenkins for CI/CD and quality gates.
• Generative AI fluency (must-have): practical experience using coding assistants to accelerate delivery, crafting prompts, checking/ground-truthing outputs, and safely handling code/data (privacy & IP). Bonus: generating test data/cases, PR summaries, or simple internal automations; exposure to vendor AI features or no/low-code connectors
• Strong API design & documentation; SOAP familiarity is a plus.
• Solid engineering practices: OOP, SOLID, data structures/algorithms, Git, reviews, reproducible builds.
• Azure/DevOps exposure desirable (pipelines, IaC basics, monitoring).
• Automation mindset: linters/formatters, build/deploy scripts, DB migrations, scaffolding/code-gen.
• Clear communicator; collaborates well with Product/QA/Ops; change agent within 6–12 months.
• Nice to have: Insurance domain exposure (claims/policy/billing/underwriting).
• Hybrid role (we just built a brand-new office space!)

The ideal candidate will analyze, review, and implement changes to websites so they are optimized for search engines. This candidate will be able to implement actionable strategies that will improve site visibility.

• ResponsibilitiesReview and analyze client sites for areas needing improvement
• Prepare detailed strategy reports
• Create and launch campaigns
• Improve clients 'rank' in major search engines

Qualifications

• Bachelor's degree in Information Technology or related field
• 3+ years' of technical experience
• Strong analytical skills
• Understanding of all search engines and functions as well as marketing

Required Skills:

1. Strong BA with presentation skills
2. US Customer Engagement experience
3. Self-driven – should be able to independently work towards the business objective.
4. Should have past experience of program management
5. Strong communication skills.
6. Must be flexible to work in overlapping times with US PST timezone.