Golang Developer

Role & Responsibilities

Own the Client’s Outcome:

• Embed with enterprise customers – on-site and remotely – to understand their supply chain operations, data estate, and what success actually looks like for their business.
• Scope and design technical solutions for messy, real-world logistics problems – with a clear line to measurable impact: cost per delivery, SLA performance, empty kilometres.
• Own the full deployment lifecycle: architecture through go-live through steady-state. You’re accountable for the outcome, not just the code.

Build and Ship:

• Design, build, and maintain backend services in Node.js or Python that power routing, planning, and execution at enterprise scale.
• Build and own the integrations connecting Locus to client ERPs, TMS, WMS, and OMS platforms – these integrations are often the riskiest part of a deployment.
• Write production code that runs under real load. If it isn’t in production, it hasn’t shipped.

Be the Technical Interface with the Client:

• Run architecture reviews, lead integration workshops, and represent Locus in executive steering meetings. You need to be credible at every level of the client organisation.
• Bring field learnings back into the product and platform teams. Some of Locus’s best features started as a client workaround.
• Push back when a client request would compromise platform integrity – and propose a better alternative.

Show Up On-Site:

• Travel to client sites – domestic and international, up to ~30% of the time – for kick-offs, integration sprints, go-lives, and post-live reviews.
• Build the kind of relationship where the client’s ops lead calls you directly when something goes wrong at 2am, not a support ticket.
• Be comfortable wherever the work is: a warehouse floor, a logistics control tower, a C-suite boardroom.

Make the Next Deployment Easier:

• Document architecture decisions, integration patterns, and deployment playbooks – every engagement should make the next one faster.
• Work closely with Product, Customer Success, and Platform Engineering. Share what you’re seeing in the field; don’t wait to be asked.
• Mentor junior FDEs and raise the technical bar across the team.

Ideal Candidate

• Strong Forward Deployed / Field Engineer
• Mandatory (Experience 1): Must have 5+ years of backend engineering experience with hands-on coding in Node.js or Python, building production-grade systems
• Mandatory (Experience 2): Must have minimum 2+ years in client-facing / deployment-heavy roles, where they worked directly with enterprise customers
• Mandatory (Experience 3): Must have experience shipping and owning production systems end-to-end: From design → build → deployment → post-production support
• Mandatory (Tech Skills 1 - Backend & Systems): Strong in: Node.js or Python (must-have), Building scalable backend services
• Mandatory (Tech Skills 2 - Integrations): Must have experience with: Enterprise integrations (APIs, third-party systems), Systems like ERP / TMS / WMS / OMS
• Mandatory (Tech Skills 3 - Data & Messaging): Hands-on with: Relational + NoSQL databases, Event streaming / queues (Kafka / RabbitMQ or similar)
• Mandatory (Tech Skills 4 - Cloud & Deployment): Experience with: Cloud platforms (AWS / GCP / Azure), Docker + Kubernetes (or containerised deployments)
• Mandatory (Company): Top Product companies / Startups / SaaS / platform companies

• Key Skills:
• Expert Proficiency in anyone the below programming language - Node JS, PHP or GoLang
• Expert Computer Science fundamentals like Data Structures, Algorithms, Time Complexity, and others
• Strong Microservices, REST API, Git source control, CI/CD, and other latest technology trends
• Strong System Design, DB Design proficiency
• Strong knowledge in Design Patterns, best software development practices
• Good exposure to working in Open Source stack, E-Commerce, or Fintech domain.

Experience: 5+ years production software engineering, with 2+ years working directly on LLM or agent systems in production. 

Location: Remote 

To streamline and fast-track screening, please submit your details here (if you haven’t already): https://airtable.com/appbtkr4odapnb5I6/pagqo91lKv3VJg3GT/form 

We’ll review your responses as part of the initial screening process. Please make sure you complete and submit all details through the form to be considered for the next stage. Submissions outside the form may not be considered.

Why This Role Matters

Terrabase builds agent infrastructure that enterprise customers rely on daily for SQL generation, forecasting, data analysis, and artifact delivery. Our orchestration layer routes between specialized sub-agents, manages typed handoff contracts, runs structured eval suites, and enforces correctness across every turn.

This is not a research-prototype role. You will build and evolve agent architecture, but always in service of making the system observable, typed, evaluated, recoverable, and boringly reliable in production.

What You Will Do

Own the harness architecture and middleware stack. Our LangGraph orchestrator routes between sub-agents through a layered middleware stack: file upload handling, source resolution, local context, workspace sync, state hydration, aggregation barriers, and typed handoff contracts. You will extend this stack, enforce its contracts in code, and keep it operational as routing logic and agent surfaces evolve.

Maintain typed contracts and boundaries. Agent handoffs at Terrabase carry typed contracts with barrier conditions and retry predicates. You will design these contracts, enforce them with strict typing, manage backward compatibility when contracts change, and write the contract tests that prevent silent regressions.

Own the eval suites. We run structured eval suites across routing decisions, context-resolution accuracy, multi-turn coherence, visual reference alignment, and artifact correctness. You will extend coverage, write new evals where gaps exist, and build CI gates that block releases when regressions are detected. A routing change or prompt change with no eval coverage does not ship.

Triage production failures and close the loop. When an agent turn fails in production, you will trace it in LangSmith, identify the failure class, and convert it into a durable regression test. You will own the release gates, keep prompts and runtime contracts in sync, manage feature flag rollout risk, and remove dead paths as the system evolves.

Own SQL and artifact correctness. Our agents generate SQL over customer schemas and produce structured artifacts (reports, dashboards, data sheets) under a strict schema contract. You will own the correctness layer: source grounding, schema-aware validation, provenance surfaces, and the eval infrastructure that catches generated artifact failures before they reach customers.

Build and maintain HITL workflows. Human-in-the-loop checkpoints let users intervene, redirect, or approve mid-chain. You will design these workflows, enforce their resumable state contracts, and ensure they degrade gracefully when interrupted.

Instrument for traceability. You will extend LangSmith tracing coverage, add structured span annotations, and build the tooling that lets us diagnose a bad agent turn from production trace data alone, without requiring a local reproduction.

What We Are Looking For

• 5+ years production software engineering, with strong Python fundamentals
• 2+ years working hands-on with LLM-based systems: agent loops, tool use, context management, or inference pipelines
• Experience with LangGraph, LangChain, OpenAI/Anthropic tool-use systems, or equivalent multi-step agent/runtime orchestration
• Practical eval engineering: you have built or extended eval harnesses, written automated test cases for agent behavior, and treated evaluation as an ongoing engineering discipline
• Strong engineering hygiene: strict typing, small interfaces, contract tests, clear schema migrations, and CI discipline
• Ability to debug from production traces and artifacts, not only local reproductions
• Comfort working across prompts, Python runtime code, TypeScript product surfaces, data systems, and eval infrastructure
• Systems thinking: you design for observability, recovery, and state management, not just the happy path
• Maintenance ownership mindset: you triage, close loops, and leave systems more debuggable than you found them
• Pragmatic judgment: you can distinguish between reliability-critical infrastructure and speculative abstraction

Bonus Points

• HITL workflow design: checkpoints, approvals, mid-chain interrupts, resumable state
• Context engineering depth: chunking strategies, retrieval-augmented generation, semantic routing, re-ranking
• Experience with LangSmith, Weights and Biases, or similar trace and evaluation platforms
• Prior work shipping agent systems to enterprise customers where SQL or data correctness is a hard requirement
• Experience with mypy, Pydantic contracts, or strict typing disciplines in a production Python codebase

Life at Terrabase

We are a sharp, focused, fully remote team building agent infrastructure that enterprise customers trust with their data. You will work directly alongside the engineer who designed this harness, with broad ownership, generous compute budgets, and a culture that treats reliability as a product requirement, not a research topic.

Terrabase is an equal-opportunity employer. We celebrate diversity and are committed to building an inclusive environment for every team member.

• You solve problems at their root, stepping back to understand the broader context.
• You develop pragmatic solutions and build flexible systems that balance engineering complexity and timely delivery, creating business impact.
• You understand a broad range of data structures and algorithms and apply them to deliver high-performing applications.
• You recognize and use design patterns to solve business problems.
• You understand how operating systems work, perform and scale.
• You continually align your work with Amazon’s business objectives and seek to deliver business value.
• You collaborate to ensure that decisions are based on the merit of the proposal, not the proposer.
• You proactively support knowledge-sharing and build good working relationships within the team and with others in Amazon.
• You communicate clearly with your team and with other groups and listen effectively.

Azure DE

Primary Responsibilities -

• Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage.
• Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure Create data models for analytics purposes
• Utilizing Azure Data Factory or comparable technologies, create and maintain ETL (Extract, Transform, Load) operations
• Use Azure Data Factory and Databricks to assemble large, complex data sets
• Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability of the data.
• Ensure data security and compliance
• Collaborate with data engineers, and other stakeholders to understand requirements and translate them into scalable and reliable data platform architectures

Required skills:

• Blend of technical expertise, analytical problem-solving, and collaboration with cross-functional teams
• Azure DevOps
• Apache Spark, Python
• SQL proficiency
• Azure Databricks knowledge
• Big data technologies

The DEs should be well versed in coding, spark core and data ingestion using Azure. Moreover, they need to be decent in terms of communication skills. They should also have core Azure DE skills and coding skills (pyspark, python and SQL).

Out of the 7 open demands, 5 of The Azure Data Engineers should have minimum 5 years of relevant Data Engineering experience.

Job Description for Senior Python Developer 

Experience: 4 to 7 years

• Must have strong knowledge in Python 2/Python 3
• Must have a strong knowledge of Web development using the Django web framework and API development experience using Django REST API.
• Flask framework or any other framework’s knowledge is great.
• Ability to write reusable, testable, and efficient code
• Team Handling exposure
• Knowledge of Standard databases like MySql, PostgreSQL and NoSQL databases like MongoDB, Firebase, etc. Able to create database schemas that represent and support business processes.
• Understanding of fundamental design principles behind a scalable application
• Must be good at understanding client requirements.
• Good testing/debugging skills using standard python modules/IDEs
• Deployment experience with standard servers like Apache/AWS etc.
• Experience in testing frameworks known in the industry.
• Having good/basic knowledge of Front end Technologies HTML, CSS, Bootstrap, JavaScript is good.
• Proficient understanding of code versioning tools - GIT

The candidate must have experience in coding part and team handling experience both

Job description 

• Lead design, development, implementation and maintenance of applications & back-end  services demonstrating service-oriented architecture. 
• Design, build, test, and maintain scalable APIs, services, and systems within the  platform. 
• Choose the right Data Structures, tools, and tech stacks and do high-level design with guidance. 
• Build, develop, mentor, review code and coach junior team members. 
• Extensive programming experience with cross-platform development: Java/SpringBoot,  Javascript/Node.js, Express.js or Python 
• Extensive knowledge of ElasticSearch, MongoDB or Cassandra, Redis, SQS and data  streaming (Spark, Flink, Kafka streams, storm, etc.). 
• Well versed in Kafka Understanding cloud native technologies such as Docker and  Kubernetes, capable to cover full development lifecycle including CI/CD 
• Experience in use of source code management system like GIT, bitbucket and build tools  like ant, maven, Gradle or make. 
• Take great pride in Code quality and developer productivity. 
• Put in Microservcies architecture in place that paves road for scalability, efficiency,  observability, and availability. 
• Build (and open source) data processing, storage and fetch systems at the petabyte scale  with the lowest cost/GB while still responding in milliseconds at the 99th percentile. 
• Write algorithms and services to influence personalisation and recommendation from a  real-time recommendation engine for both home feed to surface most viral videos +  video e-commerce 
• Build machine learning pipelines using Kinesis,Spark/Flink/TensorFlow etc 
• Agile methodologies, Sprint management, Roadmap, Mentoring, Documenting, Software  architecture 
• Proven experience in handling large infrastructure and distributed systems Liaison with Product Management, DevOps, QA, Client and other teams Your Experience Across The Years in the Roles You’ve Played 

• Have total or more 7 - 9 years of experience with 2-3 years in a startup. Have B.Tech or M.Tech or equivalent academic qualification from premier institute. Experience in Product companies working on Internet-scale applications is preferred 
• Thoroughly aware of cloud computing infrastructure on AWS leveraging cloud native  service and infrastructure services to design solutions.
• Follow Cloud Native Computing Foundation leveraging mature open source projects  including understanding of containerisation/Kubernetes. 

We Value Engineers Who Are :

• Customer-focused: We believe that doing what’s right for the creator is ultimately what  will drive our business forward. 
• Obsessed with Quality: Your Production code just works & scales linearly 
• Team players. You believe that more can be achieved together. You listen to feedback  and also provide supportive feedback to help others grow/improve. 
• Pragmatic: We do things quickly to learn what our creators desire. You know when it’s  appropriate to take shortcuts that don’t sacrifice quality or maintainability 

Chingari Benefits 

The glory. Almost too much responsibility. 

A fun-life balance 

A ticket on our rocket ship to the moon. ��