Senior AI Engineer

We’re building financial data systems that power real business decisions — and we need someone who knows how to make Django, PostgreSQL, Celery, and APIs play nicely at scale.

You know what clean, reliable backend systems look like — because you’ve built them. You’ve handled authentication quirks, rate limits, and webhooks; you build code that’s maintainable, performant, and correct.

If you’re curious about financial data, transactions, and KPIs, and enjoy turning numbers into insight, this role is for you. (Experience with banking or accounting APIs is a big plus.)

What You’ll Do

• Build and maintain Django-based systems using Celery for async and scheduled tasks
• Integrate and manage data from multiple APIs (banking, accounting, analytics, etc.)
• Design and optimize internal APIs
• Improve reliability, scalability, and performance
• Collaborate closely with product and frontend engineers

Your Profile

You’re an experienced backend engineer who is strong in all core areas of modern Python development:

• Python, Django, Django REST Framework
• Celery and asynchronous / distributed task handling
• PostgreSQL and robust data modeling
• Docker and containerized deployment workflows
• Unit testing (pytest or equivalent) and maintainable test structures
• Git, CI/CD, and reliable deployment automation
• API integrations (REST, OAuth, webhooks)
• Caching strategies & background job handling (preferred Redis experience)
• Solid understanding of security, permissions, and performance optimization

You’ve already built or scaled production-grade systems and can take ownership from architecture to deployment.

Experience with fintech or data integration systems is an advantage.

How We Work

We’re a small, remote-first team that values ownership over micromanagement.

You’ll have freedom in how you work — what matters is your impact.

Our daily language is English.

About finban

We’re building a platform that helps businesses understand and manage their financial performance in real time by connecting and analyzing data from banking, accounting, and analytics systems.

If you’ve built or scaled production Django systems before and love clean architecture — we’d love to see your work.

Staff Engineer - AI:

Location : India, Remote

Job Description

Egnyte is seeking an experienced Staff Software Engineer to join our Engineering department. The Engineering department builds large distributed components and services that run Egnyte's Cloud Platform. Our code serves billions of requests per day with sub-second latency in a fault-tolerant environment. We process and analyze millions of files and events daily. Some of the responsibilities for this department include Egnyte's Cloud File System, Content Classification, Content Lifecycle Management, User Behavior Analysis, Object Store, Metadata Stores, Search Systems, Recommendations Systems, Synchronization, and intelligent caching of multi-petabyte datasets. We are looking for candidates with a shared passion for building large-scale distributed systems and a keen sense for tackling complexities that come with scaling through multiple orders of magnitude.

In this role, you will (But are not limited to):

• Design and develop highly scalable and resilient cloud architecture that seamlessly integrates with on-premises systems
• Drive the team’s goals and technical direction to find and pursue technical opportunities that make Egnyte’s cloud platform more efficient
• Effectively communicate complex design and architecture details
• Understand company and industry-wide trends to help develop new technologies
• Conceptualize, develop, and implement changes that prevent key systems from becoming unreliable, under-utilized, or unsupported
• Own all aspects of critical software projects from design to implementation, QA, deployment, and monitoring

Qualifications

• BS, MS, or PhD. in Computer Science or related technical field, or equivalent practical experience
• 8-15 years of professional experience in engineering with a history of technical innovation
• Experience providing technical leadership to engineers

Bonus Qualifications (Good to Have)

• The breadth of knowledge across infrastructure domains, with the ability to reason about everything from data center machine software to database solutions to machine learning infrastructure to front-end web or mobile applications
• Demonstrated success in designing and developing large-scale, complex systems
• Expertise with multi-tenant, highly complex, cloud solutions; experience with Hybrid and/or on-premises solutions desired

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

Job Overview

Architect and build scalable, high-performance backend systems while working on mission-critical platforms that process real-time market data and portfolio analytics. The role also involves leveraging Generative AI capabilities to enhance data intelligence, automation, and user-facing features, while ensuring regulatory compliance and secure financial transactions.

Key Responsibilities

• Design, develop, and maintain scalable backend services and APIs using NodeJS and Python
• Build event-driven architectures using RabbitMQ and Kafka for real-time data processing
• Develop and manage data pipelines integrating PostgreSQL and BigQuery for analytics and warehousing
• Integrate and deploy Generative AI models (LLMs, embeddings, AI APIs) into backend systems for automation, insights, and intelligent workflows
• Design AI-powered features such as recommendation systems, document processing, or conversational interfaces
• Ensure system reliability, security, and low-latency performance for mission-critical systems
• Lead technical design discussions, conduct code reviews, and mentor junior engineers
• Optimize database queries, implement caching strategies, and improve overall system performance
• Collaborate with cross-functional teams to deliver end-to-end product features
• Implement monitoring, logging, and observability solutions

Required Skills and Qualifications

• 2+ years of professional backend development experience
• Strong expertise in NodeJS and Python for production-grade applications
• Proven experience building RESTful APIs and microservices architectures
• Experience working with Generative AI frameworks/APIs (OpenAI, LangChain, vector databases, prompt engineering)
• Understanding of integrating LLMs into production systems (RAG, embeddings, fine-tuning basics)
• Strong proficiency in PostgreSQL, including query optimization and schema design
• Hands-on experience with RabbitMQ and Kafka
• Experience with BigQuery or similar data warehousing solutions
• Solid understanding of distributed systems, scalability patterns, and high-traffic applications
• Strong knowledge of authentication, authorization, and security best practices
• Experience with Git, CI/CD pipelines, and modern development workflows
• Excellent problem-solving and debugging skills
• Exposure to fintech or financial services, cloud platforms (GCP/AWS/Azure), Docker/Kubernetes, caching tools (Redis/Memcached), and regulatory requirements (KYC, compliance, data privacy) is a plus

Apply directly at: https://wohlig.keka.com/careers/jobdetails/136351

About the Role

We are looking for a highly skilled Senior Java Developer with 8+ years of experience in designing, developing, and implementing enterprise-grade applications. The ideal candidate should have strong expertise in Java-based technologies along with practical experience in AI-powered applications, Generative AI, Machine Learning integrations, or AI frameworks. This role will involve working closely with cross-functional teams to build scalable, high-performance solutions leveraging modern AI technologies.

Technical Skills

• 8+ years of hands-on experience in Java development.
• Strong expertise in:
• Java 8/11/17
• Spring Boot
• Microservices Architecture
• RESTful APIs
• Hibernate/JPA
• Multithreading & Concurrency
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Solid understanding of containerization technologies such as Docker and Kubernetes.
• Experience with CI/CD pipelines and DevOps practices.

Job Title: AI/ML Engineer – Voice (2–3 Years)

Location: Bengaluru (On-site)

Employment Type: Full-time

About Impacto Digifin Technologies

Impacto Digifin Technologies enables enterprises to adopt digital transformation through intelligent, AI-powered solutions. Our platforms reduce manual work, improve accuracy, automate complex workflows, and ensure compliance—empowering organizations to operate with speed, clarity, and confidence.

We combine automation where it’s fastest with human oversight where it matters most. This hybrid approach ensures trust, reliability, and measurable efficiency across fintech and enterprise operations.

Role Overview

We are looking for an AI Engineer Voice with strong applied experience in machine learning, deep learning, NLP, GenAI, and full-stack voice AI systems.

This role requires someone who can design, build, deploy, and optimize end-to-end voice AI pipelines, including speech-to-text, text-to-speech, real-time streaming voice interactions, voice-enabled AI applications, and voice-to-LLM integrations.

You will work across core ML/DL systems, voice models, predictive analytics, banking-domain AI applications, and emerging AGI-aligned frameworks. The ideal candidate is an applied engineer with strong fundamentals, the ability to prototype quickly, and the maturity to contribute to R&D when needed.

This role is collaborative, cross-functional, and hands-on.

Key Responsibilities

Voice AI Engineering

• Build end-to-end voice AI systems, including STT, TTS, VAD, audio processing, and conversational voice pipelines.
• Implement real-time voice pipelines involving streaming interactions with LLMs and AI agents.
• Design and integrate voice calling workflows, bi-directional audio streaming, and voice-based user interactions.
• Develop voice-enabled applications, voice chat systems, and voice-to-AI integrations for enterprise workflows.
• Build and optimize audio preprocessing layers (noise reduction, segmentation, normalization)
• Implement voice understanding modules, speech intent extraction, and context tracking.

Machine Learning & Deep Learning

• Build, deploy, and optimize ML and DL models for prediction, classification, and automation use cases.
• Train and fine-tune neural networks for text, speech, and multimodal tasks.
• Build traditional ML systems where needed (statistical, rule-based, hybrid systems).
• Perform feature engineering, model evaluation, retraining, and continuous learning cycles.

NLP, LLMs & GenAI

• Implement NLP pipelines including tokenization, NER, intent, embeddings, and semantic classification.
• Work with LLM architectures for text + voice workflows
• Build GenAI-based workflows and integrate models into production systems.
• Implement RAG pipelines and agent-based systems for complex automation.

Fintech & Banking AI

• Work on AI-driven features related to banking, financial risk, compliance automation, fraud patterns, and customer intelligence.
• Understand fintech data structures and constraints while designing AI models.

Engineering, Deployment & Collaboration

• Deploy models on cloud or on-prem (AWS / Azure / GCP / internal infra).
• Build robust APIs and services for voice and ML-based functionalities.
• Collaborate with data engineers, backend developers, and business teams to deliver end-to-end AI solutions.
• Document systems and contribute to internal knowledge bases and R&D.

Security & Compliance

• Follow fundamental best practices for AI security, access control, and safe data handling.
• Awareness of financial compliance standards (plus, not mandatory).
• Follow internal guidelines on PII, audio data, and model privacy.

Primary Skills (Must-Have)

Core AI

• Machine Learning fundamentals
• Deep Learning architectures
• NLP pipelines and transformers
• LLM usage and integration
• GenAI development
• Voice AI (STT, TTS, VAD, real-time pipelines)
• Audio processing fundamentals
• Model building, tuning, and retraining
• RAG systems
• AI Agents (orchestration, multi-step reasoning)

Voice Engineering

• End-to-end voice application development
• Voice calling & telephony integration (framework-agnostic)
• Realtime STT ↔ LLM ↔ TTS interactive flows
• Voice chat system development
• Voice-to-AI model integration for automation

Fintech/Banking Awareness

• High-level understanding of fintech and banking AI use cases
• Data patterns in core banking analytics (advantageous)

Programming & Engineering

• Python (strong competency)
• Cloud deployment understanding (AWS/Azure/GCP)
• API development
• Data processing & pipeline creation

Secondary Skills (Good to Have)

• MLOps & CI/CD for ML systems
• Vector databases
• Prompt engineering
• Model monitoring & evaluation frameworks
• Microservices experience
• Basic UI integration understanding for voice/chat
• Research reading & benchmarking ability

Qualifications

• 2–3 years of practical experience in AI/ML/DL engineering.
• Bachelor’s/Master’s degree in CS, AI, Data Science, or related fields.
• Proven hands-on experience building ML/DL/voice pipelines.
• Experience in fintech or data-intensive domains preferred.

Soft Skills

• Clear communication and requirement understanding
• Curiosity and research mindset
• Self-driven problem solving
• Ability to collaborate cross-functionally
• Strong ownership and delivery discipline
• Ability to explain complex AI concepts simply

Job Title: AI Engineer

Location: Bengaluru 

Experience: 3 Years 

Working Days: 5 Days

About the Role

We’re reimagining how enterprises interact with documents and workflows—starting with BFSI and healthcare. Our AI-first platforms are transforming credit decisioning, document intelligence, and underwriting at scale. The focus is on Intelligent Document Processing (IDP), GenAI-powered analysis, and human-in-the-loop (HITL) automation to accelerate outcomes across lending, insurance, and compliance workflows.

As an AI Engineer, you’ll be part of a high-caliber engineering team building next-gen AI systems that:

• Power robust APIs and platforms used by underwriters, credit analysts, and financial institutions.
• Build and integrate GenAI agents.
• Enable “human-in-the-loop” workflows for high-assurance decisions in real-world conditions.

Key Responsibilities

• Build and optimize ML/DL models for document understanding, classification, and summarization.
• Apply LLMs and RAG techniques for validation, search, and question-answering tasks.
• Design and maintain data pipelines for structured and unstructured inputs (PDFs, OCR text, JSON, etc.).
• Package and deploy models as REST APIs or microservices in production environments.
• Collaborate with engineering teams to integrate models into existing products and workflows.
• Continuously monitor and retrain models to ensure reliability and performance.
• Stay updated on emerging AI frameworks, architectures, and open-source tools; propose improvements to internal systems.

Required Skills & Experience

• 2–5 years of hands-on experience in AI/ML model development, fine-tuning, and building ML solutions.
• Strong Python proficiency with libraries such as NumPy, Pandas, scikit-learn, PyTorch, or TensorFlow.
• Solid understanding of transformers, embeddings, and NLP pipelines.
• Experience working with LLMs (OpenAI, Claude, Gemini, etc.) and frameworks like LangChain.
• Exposure to OCR, document parsing, and unstructured text analytics.
• Familiarity with model serving, APIs, and microservice architectures (FastAPI, Flask).
• Working knowledge of Docker, cloud environments (AWS/GCP/Azure), and CI/CD pipelines.
• Strong grasp of data preprocessing, evaluation metrics, and model validation workflows.
• Excellent problem-solving ability, structured thinking, and clean, production-ready coding practices.

Experience: 8+ years, senior candidates only | Type: Full-time | Location: Remote (India)

 ---

 WHAT WE'RE BUILDING

 See http://www.juliet.space

 We're building Juliet, an AI that runs marketing end to end. Our users are marketers, founders, CEOs, growth leads, agencies, and SMBs — not developers. They

 tell Juliet the goal. She plans, writes production code, and ships real marketing: conversion-optimized websites, launch assets, campaigns, audits, autonomously.

 That's the engineering problem in one line: the humans in the loop can't read code, so the agent has to get it right on her own — plan, build, self-correct,

 recover, ship.

 Under the hood: a browser-based studio backed by cloud sandboxes, a real-time SSE streaming pipeline, and a LangGraph agent working across 83 tools and 63 skill

 modules. The agent isn't bolted onto the product. She is the product.

 Small team, big ambitions. You'll ship things users touch daily, not write tickets about them.

 ---

 THE ROLE

 We're hiring one architect-level backend engineer to own Juliet's agentic infrastructure end to end. That means the agent graph, the execution environment, the

 streaming pipeline, the state and memory systems — and setting technical direction for the engineers working alongside you.

 This is a player-coach seat. You'll still write code every day, and your architectural calls become the product. You'll work directly with the founder. No PMs in

 between.

 Frontend is part of the system. You won't be leading it, but you'll need to understand how the agent's output reaches the browser and be able to ship full-stack

 features when needed.

 ---

 THE STACK

 AI agent (primary): Python 3.11, LangGraph 1.x + LangChain, Anthropic / Google / OpenAI model providers

 API (primary): NestJS 11, Supabase, Redis, PostgreSQL, Server-Sent Events

 Infra (primary): Modal cloud sandboxes, Docker, Netlify deployments

 Frontend (secondary): Next.js 15, React 19, TypeScript, Zustand, CodeMirror 6, XTerm.js

 Monorepo: Turborepo, pnpm

 ---

 WHAT YOU'LL WORK ON

 The majority of your time is here:

 Agentic AI workflows — Design, extend, and harden the LangGraph agent graph: multi-step planning, code generation, tool dispatch, self-correction, and recovery

 across 83 tools and 63 skill modules. This is the core of the product.

 Real-time streaming architecture — The SSE pipeline that carries every agent action from the Python backend through NestJS to the browser: event framing,

 reconnection, health monitoring, interrupt handling for plan approvals and clarifying questions.

 Agent execution environments — Sandbox lifecycle on Modal: container spin-up, file sync, terminal I/O, command execution, and live preview with per-asset esbuild

 bundling. The agent lives here.

 State and memory systems — LangGraph Postgres checkpointers, middleware-injected context (goals, design docs, memory anchors), conversation summarization. How

 the agent knows what it knows.

 Backend API and data layer — NestJS services, Supabase schema, Redis caching, quota enforcement, webhook handling. The plumbing the agent depends on.

 Marketing intelligence pipelines — AEO, CRO, and brand-perception audit engines: multi-LLM probing, parallel inference, streamed structured reports, result

 caching. Audit-at-scale infrastructure.

 The remaining ~25% of your time:

 Full-stack product features — Collaboration (roles and permissions), the Netlify deployment pipeline, subscription and quota flows, onboarding. You'll ship these

 end to end — backend first, frontend to close the loop.

 ---

 WHAT WE'RE LOOKING FOR

 Must-have:

 - 8+ years of professional software engineering, including meaningful time as a tech lead or systems architect who owned something end to end. Closer to ten is

 the norm for people who thrive here.

 - Both worlds on your resume: engineering rigor inside a large company and 0-to-1 ownership at an early-stage startup.

 - Production agentic systems experience. You've built and operated LLM agent systems in production with LangGraph, LangChain, or equivalent — agent graphs, tool

 use, state management, prompt engineering, evals. This means well beyond calling a chat endpoint.

 - Strong Python. You design and ship production Python daily. The agent codebase is yours to own.

 - Architect-level system design. You can own how data flows across four services, make tradeoffs under uncertainty, and defend every call.

 - AI-native development workflow. You drive Claude Code, Codex, or similar agentic tools as everyday instruments — not occasionally. You have opinions about

 working with coding agents because you do it constantly.

 - Real-time backend systems. You've built SSE, WebSocket, or streaming API infrastructure in production — not just consumed it.

 - Strong TypeScript. The API layer and most product features are in TypeScript. You're productive in it.

 Strong plus:

 - Background in developer tools, IDEs, or coding/execution platforms

 - Container runtimes and sandboxed execution (Modal, E2B, Firecracker, or similar)

 - Depth in PostgreSQL, Redis, and Supabase

 - LLM observability and evals tooling (LangSmith or similar)

 - NestJS or equivalent Node.js API framework experience

 - React/Next.js — enough to ship a full-stack feature without handoff

 - Exposure to marketing, growth, or publisher-facing products

 ---

 WHY THIS ROLE IS DIFFERENT

 You own the architecture. Not a feature factory. Not someone else's design doc. The technical execution of an AI product is yours to lead.

 The agent is the product. You're not adding AI to an existing system. You're building and operating the system that is the AI. Every architectural decision

 touches what Juliet can and can't do.

 Hard problems, always. The system spans cloud sandboxes, streaming infrastructure, multi-step agent graphs, and a full-stack web product — for non-technical

 users who can't course-correct a broken output. The bar is high.

 Small team, real leverage. Your code ships to users the same week. No layers of approval.

 ---

 HOW TO APPLY

 Send us:

 1. A short note on the most complex agentic system you've shipped: what broke, and what you'd redo. A link to something you've built that involves agent graphs, tool use, or autonomous multi-step execution

 2. What is one thing you would improve about Juliet? It could be a feature or a bug.

What you’ll be doing

 Weare much more than our job descriptions, but here is where you will begin:

 As a Senior Software Engineer Data & ML You’ll Be:

 ● Architect, design, test, implement, deploy, monitor and maintain end-to-end backend

 services. You build it, you own it.

 ● Work with people from other teams and departments on a day to day basis to ensure

 efficient project execution with a focus on delivering value to our members.

 ● Regularly aligning your team’s vision and roadmap with the target architecture within your

 domain and to ensure the success of complex multi domain initiatives.

 ● Integrate already trained ML and GenAI models (preferably GCP in services.

ROLE:

 Whatyou’ll need,

 Like us, you’ll be deeply committed to delivering impactful outcomes for customers.

 What Makes You a Great Fit

 ● 5 years of proven work experience as a Backend Python Engineer

 ● Understanding of software engineering fundamentals OOPS, SOLID, etc.)

 ● Hands-on experience with Python libraries like Pandas, NumPy, Scikit-learn,

 Lang chain/LLamaIndex etc.

 ● Experience with machine learning frameworks such as PyTorch or TensorFlow, Keras, being

 proficient in Python

 ● Hands-on Experience with frameworks such as Django or FastAPI or Flask

 ● Hands-on experience with MySQL, MongoDB, Redis and BigQuery (or equivalents)

 ● Extensive experience integrating with or creating REST APIs

 ● Experience with creating and maintaining CI/CD pipelines- we use GitHub Actions.

 ● Experience with event-driven architectures like Kafka, RabbitMq or equivalents.

 ● Knowledge about:

 o LLMs

 o Vector stores/databases

 o PromptEngineering

 o Embeddings and their implementations

 ● Somehands-onexperience in implementations of the above ML/AI will be preferred

 ● Experience with GCP/AWS services.

 ● You are curious about and motivated by the future trends in data, AI/ML, analytics

About Corridor Platforms

Corridor Platforms is a leader in next-generation risk decisioning and responsible AI governance, empowering banks and lenders to build transparent, compliant, and data-driven solutions. Our platforms combine advanced analytics, real-time data integration, and GenAI to support complex financial decision workflows for regulated industries.

Role Overview

As a Backend Engineer at Corridor Platforms, you will:

• Architect, develop, and maintain backend components for our Risk Decisioning Platform.
• Build and orchestrate scalable backend services that automate, optimize, and monitor high-value credit and risk decisions in real time.
• Integrate with ORM layers – such as SQLAlchemy – and multi RDBMS solutions (Postgres, MySQL, Oracle, MSSQL, etc) to ensure data integrity, scalability, and compliance.
• Collaborate closely with Product Team, Data Scientists, QA Teams to create extensible APIs, workflow automation, and AI governance features.
• Architect workflows for privacy, auditability, versioned traceability, and role-based access control, ensuring adherence to regulatory frameworks.
• Take ownership from requirements to deployment, seeing your code deliver real impact in the lives of customers and end users.

Technical Skills

• Languages: Python 3.9+, SQL, JavaScript/TypeScript, Angular
• Frameworks: Flask, SQLAlchemy, Celery, Marshmallow, Apache Spark
• Databases: PostgreSQL, Oracle, SQL Server, Redis
• Tools: pytest, Docker, Git, Nx
• Cloud: Experience with AWS, Azure, or GCP preferred
• Monitoring: Familiarity with OpenTelemetry and logging frameworks

Why Join Us?

• Cutting-Edge Tech: Work hands-on with the latest AI, cloud-native workflows, and big data tools—all within a single compliant platform.
• End-to-End Impact: Contribute to mission-critical backend systems, from core data models to live production decision services.
• Innovation at Scale: Engineer solutions that process vast data volumes, helping financial institutions innovate safely and effectively.
• Mission-Driven: Join a passionate team advancing fair, transparent, and compliant risk decisioning at the forefront of fintech and AI governance.

What We’re Looking For

• Proficiency in Python, SQLAlchemy (or similar ORM), and SQL databases.
• Experience developing and maintaining scalable backend services, including API, data orchestration, ML workflows,  and workflow automation.
• Solid understanding of data modeling, distributed systems, and backend architecture for regulated environments.
• Curiosity and drive to work at the intersection of AI/ML, fintech, and regulatory technology.
• Experience mentoring and guiding junior developers.

Ready to build backends that shape the future of decision intelligence and responsible AI?

Apply now and become part of the innovation at Corridor Platforms!

Company Overview 

McKinley Rice is not just a company; it's a dynamic community, the next evolutionary step in professional development. Spiritually, we're a hub where individuals and companies converge to unleash their full potential. Organizationally, we are a conglomerate composed of various entities, each contributing to the larger narrative of global excellence.

Redrob by McKinley Rice: Redefining Prospecting in the Modern Sales Era

Backed by a $40 million Series A funding from leading Korean & US VCs, Redrob is building the next frontier in global outbound sales. We’re not just another database—we’re a platform designed to eliminate the chaos of traditional prospecting. In a world where sales leaders chase meetings and deals through outdated CRMs, fragmented tools, and costly lead-gen platforms, Redrob provides a unified solution that brings everything under one roof.

Inspired by the breakthroughs of Salesforce, LinkedIn, and HubSpot, we’re creating a future where anyone, not just enterprise giants, can access real-time, high-quality data on 700 M+ decision-makers, all in just a few clicks.

At Redrob, we believe the way businesses find and engage prospects is broken. Sales teams deserve better than recycled data, clunky workflows, and opaque credit-based systems. That’s why we’ve built a seamless engine for:

• Precision prospecting
• Intent-based targeting
• Data enrichment from 16+ premium sources
• AI-driven workflows to book more meetings, faster

We’re not just streamlining outbound—we’re making it smarter, scalable, and accessible. Whether you’re an ambitious startup or a scaled SaaS company, Redrob is your growth copilot for unlocking warm conversations with the right people, globally.

EXPERIENCE

Duties you'll be entrusted with:

• Develop and execute scalable APIs and applications using the Node.js or Nest.js framework
• Writing efficient, reusable, testable, and scalable code.
• Understanding, analyzing, and implementing – Business needs, feature modification requests, and conversion into software components
• Integration of user-oriented elements into different applications, data storage solutions
• Developing – Backend components to enhance performance and receptiveness, server-side logic, and platform, statistical learning models, highly responsive web applications
• Designing and implementing – High availability and low latency applications, data protection and security features
• Performance tuning and automation of applications and enhancing the functionalities of current software systems.
• Keeping abreast with the latest technology and trends.

Expectations from you:

Basic Requirements

• Minimum qualification: Bachelor’s degree or more in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
• Experience with Cloud platforms (AWS, Azure, GCP).
• Strong understanding of monitoring, logging, and observability practices.
• Experience with event-driven architectures (e.g., Kafka, RabbitMQ).
• Expertise in designing, implementing, and optimizing Elasticsearch.
• Work with modern tools including Jira, Slack, GitHub, Google Docs, etc.
• Expertise in Event driven architecture.
• Experience in Integrating Generative AI APIs.
• Working experience in high user concurrency.
• Experience in scaled databases for handling millions of records - indexing, retrieval, etc.,

Technical Skills

• Demonstrable experience in web application development with expertise in Node.js or Nest.js.
• Knowledge of database technologies and agile development methodologies.
• Experience working with databases, such as MySQL or MongoDB.
• Familiarity with web development frameworks, such as Express.js.
• Understanding of microservices architecture and DevOps principles.
• Well-versed with AWS and serverless architecture.

Soft Skills

• A quick and critical thinker with the ability to come up with a number of ideas about a topic and bring fresh and innovative ideas to the table to enhance the visual impact of our content.
• Potential to apply innovative and exciting ideas, concepts, and technologies.
• Stay up-to-date with the latest design trends, animation techniques, and software advancements.
• Multi-tasking and time-management skills, with the ability to prioritize tasks.

THRIVE

Some of the extensive benefits of being part of our team:

• We offer skill enhancement and educational reimbursement opportunities to help you further develop your expertise.
• The Member Reward Program provides an opportunity for you to earn up to INR 85,000 as an annual Performance Bonus.
• The McKinley Cares Program has a wide range of benefits:
• The wellness program covers sessions for mental wellness, and fitness and offers health insurance.
• In-house benefits have a referral bonus window and sponsored social functions.
• An Expanded Leave Basket including paid Maternity and Paternity Leaves and rejuvenation Leaves apart from the regular 20 leaves per annum. 
• Our Family Support benefits not only include maternity and paternity leaves but also extend to provide childcare benefits.
• In addition to the retention bonus, our McKinley Retention Benefits program also includes a Leave Travel Allowance program.
• We also offer an exclusive McKinley Loan Program designed to assist our employees during challenging times and alleviate financial burdens.