Data Engineer – OTA & Telemetry Infrastructure

• Design and implement scalable IoT solutions from sensor to cloud, ensuring seamless integration between

vehicle hardware (fuel sensors, GPS trackers, OBD devices) and the Anytime Diesel platform

• Integrate industrial and automotive sensors, microcontrollers, and gateways with the platform

• Develop, optimize, and troubleshoot data flow using protocols such as CAN bus, Modbus, RS485, TCP, and

RTU

• Manage the full IoT device lifecycle across the fleet — provisioning, remote configuration, health monitoring,

and OTA/FOTA firmware updates

• Collaborate with software, data, and operations teams to define data models and ensure clean data ingestion for

fleet analytics

• Conduct testing, debugging, and performance analysis of embedded firmware and IoT systems using tools like

oscilloscopes and logic analyzers

• Create technical documentation — architecture diagrams, API specs, and deployment guides

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

Work Mode: Full-time, in-person

Reporting To: VP – Software

Job Description

We are looking for a hands-on Technical Lead Engineer to lead the design, development, and delivery of our Head-End System (HES), Meter Data Management (MDM), and Smart Metering platform. The role requires strong backend engineering expertise, deep understanding of smart metering and utility systems, and the ability to guide a development team through architecture, implementation, integration, testing, deployment, and production support.

The ideal candidate will have practical experience building scalable IoT or utility platforms involving smart meter communication, DLMS/COSEM protocols, real-time data acquisition, validation, event processing, command execution, and integration with enterprise systems such as billing, NMS, OMS, and analytics platforms.

Key Responsibilities

• Lead end-to-end technical development of HES, MDM, AMI/AMR, and smart metering modules.
• Design scalable backend architecture for meter communication, data ingestion, validation, processing, storage, and reporting.
• Implement and guide development of DLMS/COSEM IEC 62056 based meter communication.
• Integrate with smart meters, DCUs/gateways, billing systems, NMS, OMS, analytics systems, and third-party utility platforms.
• Lead Java/Spring Boot backend development using REST APIs, messaging queues, socket programming, and distributed system patterns.
• Design high-volume data pipelines for interval data, events, alarms, billing reads, and meter health data.
• Ensure performance, scalability, fault tolerance, database optimization, and reliable production operations.
• Mentor developers, review code, define engineering standards, and guide sprint-level technical execution.
• Work with product, project, QA, deployment, and customer teams to convert utility requirements into robust technical solutions.
• Own technical troubleshooting for production issues, performance bottlenecks, device communication failures, and integration defects.
• Prepare technical documentation, architecture diagrams, API specifications, and deployment guidelines.

Required Skills

• 6+ years of software development experience, including 3+ years in smart metering, HES, MDM, AMI, IoT, or utility platforms.
• Strong hands-on experience with Java, Spring Boot, REST APIs, JDBC/JPA, multithreading, backend system design, debugging, performance tuning, and production support.
• Practical experience with DLMS/COSEM, IEC 62056, Gurux or similar frameworks, smart meter communication, meter reads, events, commands, and remote operations.
• Strong understanding of communication protocols such as TCP/IP, socket programming, FTP/SFTP, MQTT/HTTP, and related integration patterns.
• Experience with Kafka/RabbitMQ, MySQL/MariaDB, MongoDB, Redis, ClickHouse, Apache Solr, or similar messaging and data platforms.
• Knowledge of scalable architecture, including clustering, replication, load balancing, caching, retries, failover, monitoring, and large-scale time-series data handling.
• Experience leading backend engineering teams, owning technical delivery, reviewing code, and mentoring developers.
• Preferred: experience with utility/DISCOM projects, AMISP programs, billing engines, prepaid metering, NMS/OMS, energy accounting, cloud services, CI/CD, Docker/Kubernetes, observability, and cybersecurity for smart metering systems.

Education Requirement

Bachelor’s degree in Computer Science, IT, Electronics & Communication, Electrical Engineering, or a related engineering discipline is preferred. Candidates with strong hands-on HES/MDM, AMI, DLMS/COSEM, IoT, or utility software experience may be considered even with a different academic background.

About the Role

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies. We are hiring a Backend Engineer for a dedicated client engagement building an AI-powered application builder platform.

The backend is the operational core of the product: it manages user projects and sessions, coordinates long-running AI agent workloads, maintains project state, and serves as the integration layer between the frontend, the AI system, and the underlying infrastructure.

The mandatory requirement is hands-on production experience shipping Node.js services, with end-to-end ownership of API design, data modelling, and at least one production system involving background job processing or event-driven patterns.

Responsibilities

API and service development: Design and build REST APIs in Node.js with TypeScript. Cover authentication, session management, input validation, structured error handling, streaming responses (SSE, WebSockets), and rate limiting. Maintain clean API contracts that the frontend and AI system can rely on.

Database design and management: Own PostgreSQL schema design for product domains including user accounts, projects, file trees, session state, and generated artefacts. Write efficient queries, manage migrations, and optimise for read patterns that serve a real-time editor experience.

Caching strategy: Implement and maintain caching with Redis for session data, project state, and frequently read configuration. Design cache invalidation logic that keeps the editor experience consistent without stale reads.

Queue and background job management: Implement and operate background job infrastructure using BullMQ or equivalent. AI agent runs are long-running and stateful; handle retries, failure states, priority queues, and concurrency limits.

AI system integration: Build the integration layer between the backend and the AI agent system. Manage job dispatch, result handling, streaming output to the frontend, and error propagation.

Multi-tenancy and access control: Implement tenant data isolation, RBAC, and resource ownership enforcement across all API surfaces.

Observability and reliability: Instrument services with structured logging, metrics, and tracing. Write defensive code with sensible timeouts, fallback behaviour, and circuit breaking on external dependencies.

Testing and code quality: Write unit and integration tests for the services you ship. Review the work of peers and contribute to shared engineering conventions.

Requirements

• Hands-on production Node.js experience (mandatory) — must have personally shipped at least one feature area end to end in a production Node.js service, owning API design, data modelling, and testing.

• 3 to 5 years of professional backend engineering experience. Candidates with slightly less time but strong demonstrated ownership are welcome to apply.

• Strong Node.js and TypeScript. Production experience with Express, NestJS, or Fastify. Solid with async patterns, streaming, error handling, and building services that run reliably under sustained load.

• PostgreSQL depth. Schema design, query writing, indexing, and migrations on at least one production system.

• Redis and caching. Production experience using Redis for caching and session management. Understands cache invalidation trade-offs.

• Queue and background job systems. Hands-on with BullMQ, RabbitMQ, SQS, or equivalent. Experience managing retries, dead-letter queues, job priority, and concurrency control.

• AWS working knowledge. Comfortable with EC2, S3, RDS, SQS, and IAM. Familiar with Docker and basic deployment and environment management.

• Strong written and spoken English. Able to communicate clearly with engineers across disciplines and write precise technical documentation.

Nice to Have

Experience integrating with AI or LLM services (streaming responses, structured outputs, retry patterns); WebSocket or SSE implementation for real-time features; multi-tenant SaaS product experience; GraphQL; OpenTelemetry instrumentation; prior work on developer tools or editor-style products.

We’re seeking a highly skilled, execution-focused Senior Backend Engineer with a minimum of 5 years of experience to join our team. This role demands hands-on expertise in building and scaling distributed systems, strong proficiency in Java, and deep knowledge of cloud-native infrastructure. You will be expected to design robust backend services, optimize performance across storage and caching layers, and enable seamless integrations using modern messaging and CI/CD pipelines.

You’ll be working in a high-scale, high-impact environment where reliability, speed, and efficiency are paramount. If you enjoy solving complex engineering challenges and have a passion for distributed systems, this is the right role for you.

Responsibilities—

• Design, develop, and maintain distributed backend systems at scale.
• Write high-performance, production-grade code in Java.
• Architect and optimize storage systems, ensuring efficient query performance and scalable data models.
• Implement caching strategies to reduce latency and improve system throughput.
• Build and manage services leveraging AWS cloud infrastructure.
• Develop resilient messaging pipelines using Kafka (or equivalent) for real-time data processing.
• Define and streamline CI/CD pipelines, ensuring rapid and reliable deployment cycles.
• Collaborate with product managers, frontend engineers, and DevOps to deliver end-to-end solutions.
• Monitor system performance, identify bottlenecks, and apply proactive fixes.
• Drive best practices in software engineering, testing, and code reviews. 

Requirements—

• 5+ years of experience in backend engineering, with deep hands-on coding experience.
• Strong proficiency in Java and familiarity with modern frameworks.
• Proven track record in building scalable distributed systems.
• Hands-on expertise with AWS services (e.g., EC2, S3, Lambda, DynamoDB, RDS).
• Solid understanding of messaging systems like Kafka, RabbitMQ, or similar.
• Strong grasp of query performance optimization and storage system design.
• Experience with caching solutions (Redis, Memcached, etc.).
• Familiarity with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, etc.).
• Excellent problem-solving skills and ability to thrive in fast-paced environments.
• Strong communication and collaboration skills, with a proactive mindset.

Benefits—

• Best in class salary: We hire only the best, and we pay accordingly.
• Proximity Talks: Meet other designers, engineers, and product geeks — and learn from experts in the field.
• Keep on learning with a world-class team: Work with the best in the field, challenge yourself constantly, and learn something new every day.

About us—

Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.

Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.

Role- Sr Senior Engineer 

Location -Hyderabad 

Shift -Night Shift starts from 8:30 PM IST 

About The Role

As a Senior Engineer on the team, you will own systems end to end across a high-volume, event-driven surface. You'll build the APIs and services behind key initiatives including:

- The driver comms platform — the rules engine, cohorting, and scheduling that reach drivers across SMS, push, and email

 - The onboarding funnel and applicant tracking layer, architected to support Veho's move to an in-house system over time

 - Live selling workflows that turn live offer and market-clearing data into well-timed, well-targeted driver outreach

You'll partner closely with Product, Design, Operations, and Data Science to ship tooling that scales with Veho's growth.

Responsibilities Include:

- Design, build, test, and deploy features across the driver-facing apps (driver mobile app, onboarding and registration surfaces), our GraphQL APIs, and the event-driven services behind them

 - Own a problem end to end: write the design doc your team works from, build it, roll it out behind a feature flag, and stay on it after launch until it is stable

 - Own the driver comms platform — the rules engine, cohorting, and scheduling that decide when to reach a driver over SMS, push, or email, and the delivery services behind it

 - Build the onboarding funnel and applicant tracking layer: registration and set-password flows, consent and eligibility gating, and the integrations that track where every applicant sits in the funnel

 - Build live selling workflows that consume live offer data and market-clearing signals to notify the right driver cohorts only when routes are actually claimable

 - Contribute to architectural decisions and technical design for complex, distributed systems, and architect today's comms and onboarding infrastructure so it supports the eventual in-house replacement of our third-party ATS rather than becoming throwaway work

 - Break a project into milestones your product, design, ops, and data partners can plan against

 - Write correctness-first code in an event-driven system where delivery is at-least-once and no driver may be texted twice about the same route — and where a send must never fire when there is no offer to claim

 - Improve reliability and observability in the services you own, with alerts that fire on real problems and stay quiet otherwise, so an on-call engineer is paged for a broken send pipeline and not for noise

 - Propose the engineering work your team should be doing, including the reliability, data-quality, and compliance work nobody is asking for

 - Use AI-native development workflows and tooling (Claude Code, Cursor, Copilot, and similar) as part of how you ship

 - Mentor the engineers around you, keep the team's code review bar high, and write down what you learn

What You Bring:

- 5–7+ years of experience building, testing, and deploying applications in high-traffic production environments

 - Depth in AWS serverless, including Lambda, a managed GraphQL layer such as AppSync, DynamoDB, EventBridge, and SQS

 - Experience with event-driven systems and the idempotency work that comes with at-least-once delivery — especially in a comms context where duplicate or misfired messages reach real people

 - Strong full-stack experience with TypeScript, Node.js, GraphQL, and React

 - Experience with DynamoDB single-table design

 - Experience integrating with third-party platforms and their webhooks, and keeping the data they produce in sync and trustworthy across services

 - At least one project owned through production rollout, including what broke afterward and who fixed it

 - Experience operating a service in production long enough to own its failure modes

 - Judgment about what a design costs in engineering time, dollars, and vendor commitment

 - A self-starter mindset with the ability to move quickly and ship iteratively, including on migrations, compliance obligations, and the manual steps nobody has automated yet

 - Enthusiasm for working closely with product, design, operations, data science, and support partners

-Tech Stack: AWS, TypeScript, Node.js, React, React Native, GraphQL, DynamoDB, serverless event-driven architecture; 

multi-channel comms (SMS, push, email); Firebase Auth; Statsig for experimentation; Redshift/Databricks-backed data pipelines

Preferred:

 - Experience with applicant tracking / recruiting funnels or other funnel-driven onboarding systems, and the drop-off analysis that improves them

 - Experience with experimentation and analytics infrastructure (Statsig, Fivetran, Redshift, Databricks) to measure and tune what you ship

 - Consent modeling and compliance obligations (e.g., driver terms-and-conditions and messaging consent) that span services

Role overview

The client is building a multimodal AI platform that processes multi-hour video, audio and text to generate structured insights, narratives and highlight workflows for broadcasters and media organisations.

We are seeking a Backend / Platform Engineer to design and build high-throughput media pipelines, robust APIs, and model-serving infrastructure that connect our AI engine (video perception + multimodal reasoning) to real products and customer environments.

This is not a CRUD‑only backend role.

You will work on:

• long‑running jobs
• distributed processing
• GPU inference orchestration
• storage for embeddings and metadata
• integration with AI models
• reliability and observability at scale

Key responsibilities

Media ingestion & processing pipelines

• Design and implement ingestion pipelines for multi‑hour video and audio content.
• Build microservices for frame extraction, audio processing, transcription integration and metadata generation.
• Handle long‑running, asynchronous jobs using queues, workers and robust retry strategies.
• Integrate with FFmpeg or similar tools for transcoding, segmenting and preparing media for AI models.

API & platform architecture

• Design and implement REST/gRPC APIs that expose AI model outputs (perception, multimodal alignment, narratives) to frontend and external systems.
• Define clear contracts for internal services and external integrations.
• Implement authentication, authorisation and rate‑limiting for platform endpoints.
• Ensure backward‑compatible API evolution as the product matures.

Model‑serving & AI integration

• Integrate with AI inference services (video models, multimodal models, LLM/VLM) running on GPUs or specialised infrastructure.
• Design request/response flows that handle large payloads, streaming outputs and structured results.
• Optimise throughput and latency for inference pipelines, including batching, caching and concurrency control.
• Collaborate closely with AI engineers to productionise models and debug end‑to‑end behaviour.

Storage, data models & performance

• Design data models to store embeddings, timelines, metadata, scene/shot boundaries, and narrative units.
• Work with appropriate storage technologies (SQL/NoSQL, object storage, search indices) based on access patterns.
• Implement indexing and query strategies for fast retrieval of segments, highlights and multimodal insights.
• Optimise performance for large datasets and high‑volume workloads.

Reliability, observability & operations

• Implement logging, metrics and tracing across services for debugging and monitoring.
• Set up health checks, circuit breakers and graceful degradation for critical services.
• Work with CI/CD pipelines to ensure safe, repeatable deployments.
• Collaborate on Kubernetes‑based deployments (or equivalent orchestration) for scaling services.

Requirements (must‑have)

Experience:

• 4–8 years in backend or platform engineering.
• At least 3 years working on distributed systems, high‑throughput services or complex pipelines (not just simple CRUD apps).

Languages & frameworks:

• Strong proficiency in Python or Node.js (one primary, both are a plus).
• Experience with at least one modern backend framework (FastAPI, Flask, Express, NestJS, etc.).

Distributed systems & pipelines:

• Hands‑on experience with queues and workers (e.g. Celery, RabbitMQ, Kafka, SQS, etc.).
• Experience building asynchronous, long‑running job pipelines.
• Understanding of idempotency, retries, backoff, and failure handling.

APIs & integration:

• Strong experience designing and implementing REST APIs (gRPC is a plus).
• Experience integrating with external services and handling network‑level failures.

Cloud & infrastructure:

• Experience deploying services on AWS, GCP or Azure (EC2/Compute Engine, S3/GCS, IAM, networking basics).
• Experience with Docker; exposure to Kubernetes is a strong plus.

Data & storage:

• Experience with SQL and at least one NoSQL store.
• Ability to design schemas and data models for performance and maintainability.

Engineering quality:

• Strong debugging skills across services and environments.
• Experience with unit/integration tests for backend systems.
• Clear, structured communication in English.

Nice‑to‑have

• Experience with media/video processing (FFmpeg, transcoding, segmenting).
• Experience with AI/ML model integration (serving models, handling inference requests).
• Experience with search/retrieval systems (e.g. Elasticsearch, vector databases).
• Experience with observability stacks (Prometheus, Grafana, OpenTelemetry).
• Experience working with remote teams across time zones.

What we are explicitly NOT looking for

To reduce noise and mismatches, we are not looking for:

• Pure CRUD‑only backend developers with no pipeline or distributed systems experience.
• Engineers who have only worked on small, single‑service apps without scale or complexity.
• Candidates who cannot explain trade‑offs in architecture, data modelling and reliability.
• Candidates who are uncomfortable with ownership of subsystems end‑to‑end.

Why join us

• Work on real, complex problems at the intersection of media, AI and distributed systems.
• Collaborate with senior AI engineers working on perception, multimodal fusion and narrative reasoning.
• Build the core platform that turns AI models into a usable product for broadcasters and media organisations.
• Operate with high ownership, clear expectations and direct access to the CTO.

About Jinn

Jinn is a Voice AI Tech Company. It helps businesses get better RoI specially by helping sales processes with the use of Voice AI Tech. We are adding a business line which includes an audio device that can reliably capture audio in various environments.

About role:

• This Role in a B2B SaaS startup in AI space led by 2X entrepreneurs from IIT, IIMs. Fast paced with a lot of learning and growth.
• Responsibility: Helping engineer/assemble/bring together an IoT/ hardware device that can accomplish product goals with required constraints. Great high stakes exposure for fresh grads
• Duration: 3-6 months internship || Converts to Full Time based on performance 
• Compensation (Stipend): 20-25k per month || Full time 4.5lpa - 6LPA

Ideal Profile: Interested in building a career in IoT/Tech, good communication, good discipline, solid understand of tech (AI)

Skill Sets

Look for someone who:

•⁠ ⁠Has built at least 1 IoT project end-to-end

•⁠ ⁠Knows Arduino + one of ESP32 / nRF52

•⁠ ⁠Has touched audio input (even basic)

•⁠ ⁠Is comfortable debugging hardware (this is key)

1.⁠ ⁠Embedded Systems Programming (Must-have)

•⁠ ⁠C/C++ (Arduino framework or ESP-IDF)

•⁠ ⁠Working with:

  * ESP32 OR

  * Seeed Studio XIAO BLE nRF52840 Sense

•⁠ ⁠Skills:

  * GPIO, I2S (for mic input)

  * Power modes (deep sleep, wake triggers)

  * Memory constraints (huge in audio use cases)

👉 This is the backbone. If they can’t do this well, project stalls.

2.⁠ ⁠Audio Handling + Signal Basics

•⁠ ⁠Understanding:

  * Sampling rate (16kHz vs 44.1kHz)

  * PCM audio buffers

  * Latency vs quality trade-offs

•⁠ ⁠Practical skills:

  * Using I2S microphones (INMP441, etc.)

  * Basic noise filtering

  * Voice Activity Detection (VAD)

👉 Without this, you’ll just get noisy unusable recordings.

3.⁠ ⁠Power & Hardware Basics (Often underestimated)

•⁠ ⁠LiPo battery handling

•⁠ ⁠Charging IC (TP4056 type)

•⁠ ⁠Power optimization:

  * Sleep modes

  * Sampling intervals

Many prototypes fail here (battery drains in 1 hour 😅)

4.⁠ ⁠Connectivity (BLE / WiFi)

•⁠ ⁠BLE (for XIAO nRF52840):

  * Data chunking (BLE MTU limits!)

  * Pairing + mobile relay model

•⁠ ⁠WiFi (for ESP32):

  * HTTP / WebSocket streaming

  * Retry + buffering

Trade

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.

Backend Engineer - Oddr

About Oddr

Oddr is a modern enterprise platform purpose-built for professional services firms. We handle the financial nervous system of some of the world's most demanding clients - invoicing, payments, and revenue intelligence at scale. Our systems process high-stakes, high-volume financial workflows where correctness and reliability are non-negotiable. We're a small, senior-leaning team. Engineers here own systems end to-end, make real architectural decisions, and ship things that matter.

The Role

This is a deep, hands-on individual contributor role. You'll be working on the core backend platform - designing APIs, building scalable workflows, hardening infrastructure, and setting the technical bar for the team around you. You won't be managing people, but you'll naturally

raise everyone's game through code reviews, technical guidance, and the quality of your own work. If you thrive in environments with high ownership, low bureaucracy, and genuinely hard problems, this is the role for you.

What You'll Do

Core Platform Development

Design and build reliable, scalable backend systems using .NET Core. Architect RESTful APIs and business workflow orchestration that hold up under real enterprise load. Make considered tradeoffs between correctness, performance, and maintainability.

Cloud & Infrastructure

Own backend services on Microsoft Azure - app services, databases, messaging, storage, and access management. Work closely with DevOps to improve deployment pipelines and infrastructure reliability.

CI/CD & DevOps Collaboration

Support and improve CI/CD pipelines for fast, safe deployments. Bring a production-minded perspective to automation, rollback strategies, and release confidence.

Security & Compliance

Proactively embed security into the development process - secure coding practices, data protection, access controls, and compliance awareness relevant to enterprise financial systems.

Quality & Observability

Set standards for testing (unit, integration, e2e), code review, and observability. You should care deeply about knowing when things break before customers do.

Technical Mentorship

Unblock engineers around you. Share context, raise the quality of code reviews, and help the

team develop good engineering intuition - without needing a management title to do it.

What We're Looking For

Required

• 6 -10 years of backend engineering experience with strong depth in .NET Core.

• Solid understanding of RESTful API design, service architecture, and distributed systems.

• Strong relational database skills - schema design, query optimization, indexing (PostgreSQL or SQL Server)• Security-conscious mindset with practical experience applying secure coding practices

• Ability to operate independently in a fast-moving, ambiguous environment

Strong Plus

• Experience with multi-tenant SaaS architecture and tenant isolation patterns

• Hands-on experience with Microsoft Azure (App Services, SQL, Service Bus, Key Vault, etc.)

• Experience with CI/CD tooling and deployment automation

• Background in financial systems - payments, invoicing, reconciliation, audit trails

• Exposure to event-driven architecture, background job processing,and async workflows.

• Prior experience in a tech lead, staff engineer, or equivalent hands-on senior role.

What We Offer

• Competitive salary and benefits

• A small team where your decisions actually shape the product

• Hard problems worth solving - no ticket-factory work

• Flexibility and trust to get things done your way