Recruiting Bond

Job Description

Qualified applicants with experience in the following role or comparable job titles are encouraged to apply:

• Audio AI Engineer
• Speech AI Engineer
• Audio Software Engineer
• Speech Processing Engineer
• Audio Machine Learning Engineer
• Machine Learning Engineer – Speech
• AI Engineer – Audio
• Speech Processing Engineer
• Research Engineer – Speech AI
• Research Scientist – Speech
• Speech Recognition Engineer
• ASR Engineer
• Automatic Speech Recognition Engineer
• Voice AI Engineer
• Speech Scientist
• Audio Research Engineer
• Audio Systems Engineer
• Audio Software Engineer
• Audio R&D Engineer
• Speech Research Engineer
• Audio DSP Engineer
• Voice Processing Engineer
• Acoustic AI Engineer
• Research Engineer – Speech AI
• Research Scientist – Speech
• AI Engineer – Speech
• AI Engineer – Audio

Requirement:

a) Working on Design, Development, testing and deployment of different speech enhancement products using frameworks like PyTorch and TensorFlow.

b) Working on enhancing existing speech enhancement products w.r.t

performance, low latency and less computation.

c) Work on improvement of adapting the model to multi channels.

d) Should be self-motivated to learn and explore new areas and able to work independently and contribute

Experience

a) Good understanding of signal processing and machine learning.

b) Hands-on experience with Deep Learning techniques like CNNs, RNNs, LSTMs, Transformers, etc., for speech processing is essential.

c) Good understanding of: Linear algebra, Optimization techniques, Statistics and pattern recognition

d) Minimum 3 years of work experience in the Audio/Speech domain

e) Good programming skills in C/C++, Python, AI/ML frameworks.

Qualification

Bachelor's / Master’s Degree from AI/ML, CSE, ECE, or PhD

ACCOUNT BASED MARKETING MANAGER

Marketing · Growth

📍 Noida 🕐 Full-Time 🧭 2-5 years

THE MISSION

We aren't automating scripts — we're deprecating the era of manual-heavy testing entirely. We're hiring for this mandate for one of our Port-folio Client in (B2B SaaS AI Product Company). Their AI is building the world's first AI-native platform where Agentic Intelligence autonomously plans, authors, and self-heals the entire Quality Engineering lifecycle.

Drive targeted account engagement and conversion through strategic ABM initiatives and precise budget management.

THE PILLARS OF IMPACT

🚀 1. Strategic Account Engagement (50%)

– Develop personalized campaigns for high-value accounts.

– Leverage LinkedIn ads for precise audience targeting.

– Collaborate with sales for seamless lead handoff.

– Optimize campaigns to exceed conversion targets.

⚙️ 2. Budget Management and Optimization (30%)

– Manage and optimize budgets exceeding $20,000.

– Track and report on ROI for marketing spend.

– Ensure efficient allocation of resources across campaigns.

🧠 3. Creative Development (20%)

– Design impactful landing pages for campaigns.

– Create ad creatives that drive engagement.

– Collaborate with design team for visual assets.

MUST-HAVES — DO NOT APPLY UNLESS YOU HAVE THESE

– Hands-on experience with LinkedIn ads

– Managed budgets exceeding $20,000

– Ability to create landing pages and ad creatives

THE BAR — WHAT YOU MUST PROVE

LinkedIn Ads Expertise: Successfully ran LinkedIn ad campaigns with high engagement rates.

Budget Management: Managed marketing budgets over $20,000 with a proven track record.

Creative Development: Developed landing pages and ad creatives that enhanced campaign performance.

Collaboration with Sales: Aligned marketing strategies with sales targets for improved conversions.

YOUR PATH

Reports to the VP of Marketing, working closely with the sales and design teams. In 12-18 months, potential growth into a Senior ABM Manager role, leading larger-scale initiatives and strategic planning.

Your growth at AI is mapped to what you ship — not how long you've been here.

Required Skills

LinkedIn outreach, Landing Pages, B2B SaaS Sales, LinkedIn Campaign’s, Ad creatives, LinkedIn Campaign Manager, Account Based Marketing (ABM), LinkedIn Campaign Manager, LinkedIn Ads, Demand Generation, Account Engagement

• B2B SaaS
• Enterprise Marketing
• Performance Marketing
• Paid Media
• Pipeline Generation
• Landing Page Optimization
• Conversion Rate Optimization (CRO)

Lead SDET/QA Test Automation Engineer – AI Platforms (Agentic AI)

📍 Hyderabad, India | Full-Time | On-site / Hybrid

📈 Experience: 6–10 Years

The Role

We're looking for a hands-on Lead SDET to define and scale quality engineering across our healthcare AI platform.

This is an 80% IC and 20% leadership role, focused on building next-generation testing infrastructure, establishing quality standards, and mentoring engineers.

What You'll Do

Quality Architecture

• Define company-wide quality strategy.
• Architect automation frameworks from the ground up.
• Establish testing standards and engineering practices.

AI Systems Testing

Own validation strategies for:

• LLM Applications
• Voice AI Platforms
• Conversational AI
• Agentic Systems
• Multimodal AI

Build frameworks for:

• Hallucination testing
• Safety testing
• Regression detection
• AI performance measurement

Automation Engineering

Drive testing across:

• APIs
• Databases
• Web Applications
• Mobile Applications
• Distributed Systems
• Performance Engineering

Leadership

• Mentor and guide engineers.
• Drive engineering excellence.
• Influence release and architecture decisions.

What We're Looking For

• 6–10 years in SDET or QA Automation.
• Strong product engineering background.
• Expert-level coding in Python and Java.
• Deep expertise in:
• Selenium
• Playwright
• Appium
• PyTest
• TestNG
• REST Assured
• Strong understanding of:
• Distributed Systems
• System Design
• CI/CD
• SDLC
• STLC
• Experience building automation frameworks from scratch.
• Strong mentoring and technical leadership skills.

Why Join Us?

• Own quality engineering for category-defining AI products.
• Influence engineering strategy and architecture.
• Work on cutting-edge healthcare AI systems.

Lead Mobile Engineer - Android & iOS, AI-Native Healthcare Apps

📍 Location: Hyderabad, India

📍 Work Type: Full-Time | On-site / Hybrid

📍 Experience: 5–7 Years

Role Overview

Lead design, development, and delivery of mobile apps across Android and iOS. Own architecture, quality, and mobile engineering practice. Integrate Voice AI, conversational AI, and real-time features into patient-facing healthcare applications.

Key Responsibilities

Mobile Architecture & Delivery

•    Lead architecture and development of native or cross-platform mobile apps (Android & iOS)

•    Set technical direction, coding standards, and best practices for mobile

•    Deliver performant, polished, accessible mobile experiences at scale

•    Own app release process: app store submissions, versioning, mobile CI/CD

AI & Real-Time Integration

•    Integrate Voice AI, conversational AI, and LLM-powered features into mobile

•    Build real-time patient engagement experiences (streaming, push, WebSockets)

•    Collaborate with backend, product, and design on cohesive AI experiences

Quality & SDLC

•    Monitor app performance, crashes, and user feedback; drive continuous improvement

•    Champion mobile SDLC practices: testing, CI/CD, code review, release management

•    Leverage AI coding tools (Cursor, Copilot, Claude Code) to increase velocity

Leadership & Mentorship

•    Mentor and guide mobile engineers; conduct technical reviews

•    Own mobile engineering standards and drive architectural decisions

Requirements

•    5–7 years mobile development (Android & iOS)

•    Strong native expertise: Kotlin/Java (Android) and/or Swift (iOS)

•    OR cross-platform expertise: React Native or Flutter

•    Proven mobile architecture and technical decision leadership

•    Deep mobile performance, offline support, and security knowledge

•    Full app release lifecycle and store guidelines experience

•    Track record mentoring engineers and leading delivery

•    API integration and mobile-backend communication expertise

•    Strong ownership mindset and AI-first working style

Nice-to-Have

•    AI/LLM or conversational AI features in mobile apps

•    Video stack experience: streaming, recording, real-time communication (WebRTC)

•    Real-time/streaming and push notification systems at scale

•    Mobile open-source contributions or published apps at scale

•    Healthcare technology or health-tech startup experience

Why this opportunity?

•    Build infrastructure and products powering real-world healthcare AI

•    Work with AI-native engineering teams using cutting-edge tools (Claude Code, Cursor, Copilot)

•    Mission-driven impact — improve patient outcomes and save thousands of staff hours

•    High ownership, rapid learning, and significant career upside

•    Global collaboration across India and the US

•    Seed-stage growth — scale from Seed to Series A alongside the team

About My Client Company

We're building the learning infrastructure that transforms AI agents into true digital workers. While today's agents can reason and plan, they fail to do meaningful work because they lack real experience operating in apps. My Client Product gives agents continuously improving, reusable skills across 1000+ production-grade app connectors including Gmail, Linear, and Hubspot. We handle authentication, tool routing, retries, failure handling, and observability, making every action safe and dependable.

About the Role

Every enterprise is racing to make AI work — not as a demo, but as infrastructure that runs their business. My Client Product is becoming the critical layer that makes this possible: the platform that connects AI agents to 250+ real-world applications with production-grade auth, execution, and reliability.

We've built this for the cloud. Now we need to build it for the enterprise — and that means rethinking the platform from the ground up with the right abstractions, primitives, and architectural decisions that let us serve a massive, diverse set of enterprise customers without bespoke engineering for each one. This is a founding role.

Your Impact

• Agent infrastructure platform: The foundational layer that enterprise AI agents run on — governance, observability, and control planes for MCP-powered agent ecosystems. You'll define how organizations monitor, audit, and manage AI agents operating at scale across their systems
• The integration gateway: The secure, reliable bridge between an enterprise's AI agents and the outside world — every SaaS tool, internal system, and API they need to act on. Not just connectors, but a platform-grade gateway with the right trust, permissioning, and routing primitives
• Platform primitives for scale: Multi-tenancy, isolation, configuration, and extensibility abstractions that let Composio serve thousands of enterprise customers without linear engineering cost
• Enterprise-grade architecture: Deployment flexibility, security, and compliance as first-class platform capabilities — not bolted-on afterthoughts
• The repeatable deployment motion: Turn enterprise onboarding from a services engagement into a product experience. Shorter cycles, fewer custom touches, more self-serve

What you bring

• You've built platforms at genuine scale — not just high user counts, but high complexity: many customer types, deployment models, and integration surfaces
• You think in abstractions and primitives. Your instinct is to find the right foundational model, not to solve each problem individually
• You've shipped enterprise product capabilities (deployment flexibility, security, admin tooling, compliance) and understand them as product problems, not just checkboxes
• You've built or shipped an AI product — or you're the person who can't stop tinkering. You're building agents on weekends, stress-testing the latest models, experimenting with MCP, and forming your own opinions on where agent architectures are headed. You have a point of view on this space, not just a resume line
• You're a force multiplier. When you join a team, the entire product moves faster because the platform decisions are right

Skills & Expertise

Platform Engineering, AI Infrastructure, Agentic AI, AI Agents, MCP (Model Context Protocol), Distributed Systems, Enterprise Architecture, Multi-Tenant Architecture, Backend Platform Engineering, Enterprise SaaS, API Platform Engineering, Integration Platforms, SaaS Connectors, Cloud Infrastructure, AWS, GCP, Kubernetes, Docker, Terraform, Microservices, Event-Driven Architecture, API Gateway, OAuth 2.0, RBAC, IAM, Observability, OpenTelemetry, Prometheus, Grafana, Reliability Engineering, SRE, Python, Golang, Node.js, TypeScript, REST APIs, GraphQL, AI Orchestration, LLM Infrastructure, LangChain, LangGraph, OpenAI APIs, Claude APIs, RAG, Workflow Automation, AI Tool Routing, Enterprise Security, Compliance Engineering, Deployment Architecture, Configuration Management, Extensible Systems, Scalability Engineering, High-Scale Systems, Technical Strategy, Platform Primitives, Developer Platforms, Enterprise Integrations, Infrastructure Engineering, Founding Engineer Mindset.

This role demands deep platform thinking. You've designed systems where the abstractions were the product — where getting the primitives right meant the difference between a product that scales and one that drowns in customer-specific code.

You've done this within large organizations and seen what "enterprise-grade" actually means when thousands of teams depend on your platform. But you've also operated in environments where you had to build fast, make tradeoffs, and ship before the architecture was perfect.

The combination matters. Big-company pattern recognition with small-company intensity.

What We Offer

• Lunch and dinner are provided in the office
• $200/month learning and development budget
• $1,000/month AI tool experimentation budget to automate, accelerate, and improve how you work
• High-ownership role with direct exposure to leadership and company-building decisions
• Competitive salary and equity

Company Description

Recruiting Bond International is a next-generation Talent Intelligence, Executive Search, and Human Capital Advisory firm helping start-ups, enterprises, GCCs, and VC/PE-backed companies build high-impact global teams. It is a global leader in Recruitment Process Outsourcing (RPO), executive search, and workforce consulting, specializing in building transformative talent strategies.

From high-growth startups to Fortune 500 companies, Recruiting Bond partners with organizations across 50+ industries and 140+ countries to deliver fast, scalable, and inclusive hiring solutions. The company supports businesses in scaling teams, fostering innovation, and creating talent-first strategies to achieve their goals.

With deep expertise across Technology, FinTech, Healthcare, Real Estate, and Energy, Recruiting Bond is dedicated to building careers, companies, and futures by connecting world-class talent with high-impact opportunities globally.

About the Role

Our client is hiring a Frontend Engineer in India to build the product surface for the memory platform. The seat is for an engineer with 7-10 years of experience who has internalized AI-native engineering: building with Claude Code, Codex, Cursor, Windsurf, or comparable tools as a core part of how they ship.

This role is intended for an experienced engineer with 7–10 years of Frontend engineering experience, who has deeply internalized AI-native engineering practices and actively builds using tools such as Claude Code, Codex, Cursor, Windsurf, or comparable AI development tools as a core part of their workflow.

The hiring process is intentionally non-traditional and skill-first. There is no evaluation based on IIT pedigree, LeetCode performance, or conventional resume filters. Instead, the only evaluation criterion is: how you build with AI in real-world scenarios.

Candidates are expected to submit prompt logs or transcripts from Claude Code, Codex, Cursor, or Windsurf demonstrating a feature or product they are proud of.

What You'll Own

• Build and scale the frontend product surface that customers interact with
• Ship features end-to-end, designing and debugging with AI coding tools as part of the core workflow
• Own component architecture, design system, and UX quality across the product
• Collaborate with the backend team on API design and data layer integration
• Contribute to the product roadmap based on customer feedback

Requirements

Must-Have

• 7-10 years of frontend engineering experience
• Demonstrated ability to build with AI coding tools (Claude Code, Codex, Cursor, Windsurf, or comparable)
• Ability and willingness to submit prompt log transcripts from a feature or product you are proud of
• Strong React and TypeScript fundamentals
• Strong UI/UX engineering sensibility, ships polished customer-facing surfaces
• Comfort owning frontend systems end-to-end in production
• Based in India, remote work from anywhere in the country

Nice-to-Have

• Prior AI infrastructure, developer tools, or dashboard product UI experience
• Design engineering range or strong design taste
• Open-source contributions in frontend frameworks or developer tools
• Public technical writing or conference talks on AI-native frontend engineering
• Experience with modern frontend tooling (Next.js, Tailwind, shadcn/ui, Vercel)

Company Description

Recruiting Bond International is a next-generation Talent Intelligence, Executive Search, and Human Capital Advisory firm helping start-ups, enterprises, GCCs, and VC/PE-backed companies build high-impact global teams. It is a global leader in Recruitment Process Outsourcing (RPO), executive search, and workforce consulting, specializing in building transformative talent strategies.

From high-growth startups to Fortune 500 companies, Recruiting Bond partners with organizations across 50+ industries and 140+ countries to deliver fast, scalable, and inclusive hiring solutions. The company supports businesses in scaling teams, fostering innovation, and creating talent-first strategies to achieve their goals.

With deep expertise across Technology, FinTech, Healthcare, Real Estate, and Energy, Recruiting Bond is dedicated to building careers, companies, and futures by connecting world-class talent with high-impact opportunities globally.

About the Role

Our client is hiring a Backend Engineer (India-based, Remote) to design, build, and scale the core memory infrastructure powering production-grade AI agents.

This role is intended for an experienced engineer with 7–10 years of backend engineering experience, who has deeply internalized AI-native engineering practices and actively builds using tools such as Claude Code, Codex, Cursor, Windsurf, or comparable AI development tools as a core part of their workflow.

The hiring process is intentionally non-traditional and skill-first. There is no evaluation based on IIT pedigree, LeetCode performance, or conventional resume filters. Instead, the only evaluation criterion is: how you build with AI in real-world scenarios.

Candidates are expected to submit prompt logs or transcripts from Claude Code, Codex, Cursor, or Windsurf demonstrating a feature or product they are proud of.

What You'll Own

• Build and scale backend systems powering the memory infrastructure of the product
• Own and deliver features end-to-end, integrating AI coding tools into the core development workflow
• Design, manage, and optimize database, storage, and retrieval systems for persistent memory
• Collaborate closely on system architecture, scalability, performance, and reliability engineering
• Contribute directly to product roadmap decisions based on real customer usage and production insights

Requirements

Must-Have

• 7–10 years of backend engineering experience
• Demonstrated ability to build with AI coding tools (Claude Code, Codex, Cursor, Windsurf, or comparable)
• Ability and willingness to submit prompt log transcripts from a feature or product you are proud of
• Strong Python fundamentals
• Strong PostgreSQL or comparable relational database fundamentals
• Comfort owning systems end-to-end in production
• Based in India, remote work from anywhere in the country

Nice-to-Have

• Prior AI infrastructure or developer tools product experience
• FastAPI fluency
• Open-source contributions in AI, memory, vector databases, or developer tools
• Prior experience in memory systems, RAG pipelines, or vector database engineering
• Public technical writing or conference talks on AI-native engineering practices

Director of Engineering — Flights Platform

AI-First Travel Commerce · High-Scale Distributed Systems · Marketplace Infrastructure

🌏 The Problem Space

A flight search looks trivially simple. It is anything but.

Every query you fire triggers a choreography of distributed systems operating in real-time — integrating with a dozen airline GDS/NDC providers, computing dynamic fares across inventory buckets and fare rules, ranking thousands of itineraries by relevance and business intent, and returning a ranked, priced, bookable result set — all in under 100ms.

→ Millions of search queries per minute

→ <100ms end-to-end SLA with external API dependencies

→ High-value transactions — a bug here means a missed booking, not a failed render

→ Pricing errors erode trust faster than any other failure mode

We are rebuilding the Flights platform as a real-time commerce engine for Bharat — AI-native from day zero, built to power both B2C consumer journeys and high-stakes B2B enterprise corridors.

This is a once-in-a-decade opportunity to build national-scale flight infrastructure from first principles.

🧠 What You Will Own

You will own the full Flights platform — systems, architecture, and the teams that build them.

Core System Domains:

•Search Systems — high-throughput, low-latency query pipelines returning ranked, bookable options

•Pricing & Fare Engine — dynamic pricing logic, fare rules, promotional overlays, and real-time validation

•Booking & Ticketing — transaction-critical flows requiring strict consistency, idempotency, and zero data loss

•Airline Integrations — managing unreliable external GDS/NDC APIs with retries, circuit-breakers, and reconciliation

•Post-Booking Flows — cancellations, modifications, refunds — correctness at the margin is non-negotiable

Platform Scope:

•High-scale APIs serving consumer apps, B2B enterprise clients, and third-party partners

•Event-driven state machines managing booking workflows across async boundaries

•Observability and reliability infrastructure across all mission-critical flows

Team Scope:

•Lead 15–30+ engineers across multiple product and platform teams

•Manage Engineering Managers and Principal/Staff engineers

•Own hiring, org design, and technical direction

⚙️ Core Engineering Challenges

This role is fundamentally about making the right trade-offs under uncertainty — at scale.

Latency vs. Accuracy — when do you serve a cached fare vs. call a live airline API?

Availability vs. Consistency — graceful degradation at booking time vs. strict price validation

Cost vs. Performance — when is an external API call worth it vs. a cache hit?

Scalability vs. Simplicity — the best system is the one your team can reason about under incident

🤖 AI-First Engineering

AI is not an afterthought. It is load-bearing architecture.

•LLM-powered pricing intelligence — dynamic fare prediction and demand signals

•RAG pipelines for fare rules, refund policy, and support automation

•Agentic booking resolution workflows — autonomous exception handling at scale

•MCP-based orchestration layers for multi-provider integration

⚖️ Key Responsibilities

Architecture & Distributed Systems

•Design and evolve sub-100ms distributed query systems serving millions of concurrent searches

•Build fault-tolerant booking pipelines with strong consistency and durability guarantees

•Drive Kafka-based event architectures for booking state management

Reliability & Observability

•Own 99.99%+ availability for booking and pricing systems

•Build deep observability — metrics, distributed tracing, structured logging, SLOs/SLAs

•Lead post-incident reviews and drive systemic reliability improvements

Business Partnership

•Partner with Product, Revenue, and Partnerships to translate commercial goals into architecture

•Influence platform roadmap, supplier strategy, and long-term technical investment

🛠️ Technology Stack

Backend: Java · Kotlin · Go · Python

Architecture: Microservices · Event-Driven (Kafka) · gRPC

Data: Redis · Aerospike · DynamoDB · Elasticsearch

Cloud: AWS (EKS, EC2, S3)

Observability: Prometheus · Grafana · OpenTelemetry

👤 Who You Are

•12–16 years in backend/distributed systems; 5+ Years in an Engineering Leadership role, led teams of 15–50 engineers

•Built and scaled large B2C + B2B platforms — Travel Tech, FinTech, or high-scale Consumer

•Deep expertise in real-time systems, marketplace dynamics, and external API integration

•Tier-I institute background strongly preferred (IIT / IIIT / NIT / IISC / BITS / VIT / SRM — CSE/ISE)

🚀 Why This Matters

Build national-scale infrastructure for 1.4 billion people

Sit at the intersection of AI · distributed systems · marketplace economics

Define the future of travel commerce in India — from architecture to product

🤖 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.

🧭 Tech Lead (Backend / Fullstack | 7–10 Years)

Location: Bangalore (On-Site, Hybrid)

Company Type: Public-Listed Product Company

We’re Building a “Top 1% Engineering Org”

We’re building a high-talent-density, AI-first R&D organization from scratch — inside a publicly listed company undergoing a full-scale transformation.

Think:

→ Rewriting legacy systems into AI-native architectures

→ Embedding LLMs + Agentic AI into core workflows

→ Reimagining platforms, infra, and data systems for the next decade

This is the kind of shift you’d expect from Google, Microsoft, or Meta —

Except you get to build it from day 0 → scale it globally.

About the Role / Team

We are building a next-generation AI-first R&D organization in Bengaluru, focused on solving complex problems across LLMs, Agentic AI systems, distributed computing, and enterprise-scale architectures.

This initiative is part of a publicly listed global company investing heavily in AI-driven transformation, re-architecting its platforms into intelligent, autonomous systems powered by large language models, workflows, and decision engines.

You will be working on:

• Agentic AI systems & LLM-powered workflows
• Distributed, scalable backend systems
• Enterprise-grade AI platforms
• Automation-first engineering environments

🚀 The Mandate

Lead execution of mission-critical systems while staying hands-on — bridging architecture and delivery.

🧩 What You’ll Do

• Own end-to-end delivery of complex engineering initiatives (0→1, 1→N)
• Design systems across backend + frontend (if fullstack)
• Translate ambiguous problems into structured technical solutions
• Drive engineering best practices, code quality, and velocity
• Mentor engineers and elevate team performance
• Collaborate with stakeholders on roadmap and execution strategy

🧠 What We’re Looking For

• Strong experience in backend systems + optional frontend frameworks
• Proven ability to lead projects and deliver at scale
• Solid understanding of system design and architecture patterns
• Ability to balance speed vs quality vs scalability trade-offs
• Strong communication and leadership without authority
• Strong coding skills in Python / Java / Go / Node.js
• Solid understanding of data structures, system design basics, and backend architecture
• Experience building scalable APIs and services
• Familiarity or curiosity around AI/LLMs, async systems, or event-driven design
• Strong debugging, problem-solving, and ownership mindset

Nice to Have

• Experience integrating LLMs, vector databases, or AI pipelines
• Contributions to architecture at scale
• Experience with Agentic AI / LLM orchestration frameworks
• Background in product engineering or platform companies
• Exposure to global-scale systems (millions of users / high throughput)

🔥 What Sets You Apart

• Experience leading platform builds or major system rewrites
• Exposure to AI systems, LLM integrations, or intelligent workflows
• Built platforms used by millions of users / high-throughput systems
• Experience with event-driven systems, stream processing, or infra platforms
• Prior work on AI/ML platforms, model serving, or intelligent systems

Background: We Commonly See (But Not Limited To)

• Our team often includes engineers from top-tier institutions and strong research or product company or DeepTech or AI 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.