via Jazzhr
$90K - 150K a year
Develop and scale backend architecture and APIs for a cloud-native platform with agentic AI features.
5-8+ years software engineering with backend production experience, strong Python and cloud-native data engineering skills, and interest in agentic AI.
Senior Software Engineer, Platform & Agentic Systems Reports to: Chief Technical Officer (CTO) Works closely with: Agromet Programs, Product, and external partners Location: Remote-first — preference for East Africa or European time zones Contract Type: Full-time (40h per week) Term: One-Year Fixed-Term Contract, with possibility of renewal About TomorrowNow TomorrowNow is rewriting the future of agricultural resilience. By harnessing next-generation weather and climate technology, we empower smallholder farmers to adapt and thrive amidst the challenges of climate change. From a starting base of 5 million farmers, our ambition is bold: to ultimately reach 100 million farmers with next-generation agromet advisories. As a climate-tech nonprofit, TomorrowNow combines cutting-edge innovation with on-the-ground action to deliver scalable solutions for those most affected by climate variability. Our mission is to transform how smallholder farmers access and use climate information — turning it into a powerful lever for growth, resilience, and prosperity. About the Role The Senior Software Engineer, Platform & Agentic Systems is a senior, hands-on engineering role at the heart of TomorrowNow’s technology stack. You will be responsible for the continued development, scaling, and evolution of the Global Access Platform (GAP) — our core agromet intelligence hub — and its growing agentic systems layer. GAP is going fully agentic. This role will drive that transition, building out the infrastructure, APIs, tooling, and interfaces that will enable AI agents, partner systems, and farmer-facing applications to reason over, act upon, and learn from the world’s best agricultural weather intelligence. You will work in close collaboration with our GIS and geospatial engineering partners to evolve GAP into a world-class agromet intelligence platform — one that powers farmer advisory services at scale across Africa. This is a full-stack role spanning backend platform engineering, API development, data architecture, frontend product development, and agentic AI systems design. It also carries product ownership — you will help define what gets built, not just how. We are looking for a senior software engineer who combines deep technical capability with product intuition and a genuine interest in the intersection of AI, geospatial systems, and agricultural impact. Remote-first, with preference for East Africa or European time zones. Platform Context GAP is TomorrowNow’s primary technical platform — a cloud-native, API-first system that ingests, processes, and serves weather and climate intelligence to agricultural advisory services across Africa. The platform is built on a modern Python/Django backend with cloud-native data infrastructure, including Zarr/Icechunk for forecast storage, PostGIS for geospatial data, and a growing agentic AI layer. A front-end dashboard and partner-facing interfaces are in active development. Key Responsibilities Platform Architecture & Backend Engineering Own and extend the GAP backend architecture — APIs, data pipelines, processing infrastructure, and service integrations. Design and implement scalable data ingestion and transformation pipelines for multi-source weather and climate products Evolve the Zarr/Icechunk forecast data architecture for high-performance transactional reads, writes, and versioning. Build and maintain robust REST and agent-facing APIs consumed by advisory engines, delivery partners, and AI agents Contribute to platform DevOps, deployment infrastructure, and production reliability. Implement security, authentication, and access control patterns appropriate for a multi-tenant partner platform Agentic Systems Development Lead the design and development of GAP’s agentic systems layer — building, testing, and deploying tools and services that enable AI agents to act on agromet intelligence Architect agentic workflows that enable AI agents to autonomously query, reason over, and act on agromet intelligence Implement Icechunk integration with the agentic layer for transactional, versioned forecast data access Build agent orchestration patterns, tool-use pipelines, and context management for multi-step advisory generation Ensure agentic systems are robust, well-documented, and extensible by partner engineering teams and LLM-based clients. Stay at the frontier of agentic AI systems development and introduce new patterns as the field evolves. Frontend & Product Development Design and build frontend interfaces for GAP — dashboards, partner portals, advisory visualizations, and internal tools Develop React-based (or equivalent) user interfaces that surface complex agromet intelligence in clear, actionable forms Collaborate with the agromet science team to translate advisory outputs into well-designed, farmer-centric data products Contribute to product definition — help shape the roadmap for what gets built, with a focus on partner and farmer impact. Build and maintain API documentation, developer-facing tooling, and integration guides for partner teams. Partnership & External Collaboration Serve as the primary engineering counterpart on GAP agentic systems development and platform integration Lead joint architecture and sprint planning sessions, code reviews, and technical design decisions with partner engineers. Ensure shared systems meet TomorrowNow’s standards for quality, performance, and extensibility Support technical scoping and delivery oversight for contracted development milestones Interface with other external technical partners, including the validation dashboard and station networks Quality, Documentation & Platform Operations Implement comprehensive testing strategies — unit, integration, and end-to-end — for all platform components Produce clear technical documentation for all systems: architecture diagrams, API references, integration guides, and runbooks Monitor production systems, identify performance bottlenecks, and drive continuous improvement. Contribute to internal knowledge sharing and technical mentoring across the engineering team. Role Clarity To set expectations clearly, the table below defines what this role owns, contributes to, and is not responsible for. Scope Activities This role OWNS GAP backend platform development (APIs, data pipelines, forecast infrastructure); agentic systems layer — design, development, and expansion of agent tools and services; frontend dashboard and partner interface development; technical delivery; platform documentation, testing, and production reliability This role CONTRIBUTES TO Advisory algorithm integration (with the agromet science team); agentic AI system design and LLM tooling strategy; donor-facing technical demonstrations and platform showcases; product roadmap definition and feature prioritization; platform architecture decisions (shared with CTO) What You Bring Education A bachelor’s degree (required) or MSc (advantageous) in one of the following or a closely related field: Computer Science, Software Engineering, or Computing Geoinformatics, Spatial Data Science, or Earth Observation with strong software engineering skills Data Engineering, Applied Mathematics, or Computational Science with a software specialization Experience 5–8+ years of professional software engineering experience, with at least 3 years on production backend systems Demonstrated experience building and scaling cloud-native APIs, data platforms, or geospatial systems in production Experience with agentic AI frameworks, LLM tool use, or agentic tool-serving systems, or strong demonstrable interest and rapid self-upskilling in this area Track record of owning full delivery cycles — from architecture through to deployed, production-quality software Experience collaborating with external engineering partners or contractors on shared technical delivery Exposure to geospatial, weather, climate, or agricultural data systems is a significant advantage Technical Skills Backend & Data Engineering Strong Python proficiency — production-grade backend development using Django, FastAPI, or equivalent Cloud-native data engineering: Zarr, Xarray, NetCDF, GeoTIFF, and large-scale raster/time-series pipelines Relational and geospatial databases: PostgreSQL/PostGIS REST API design, implementation, and documentation (OpenAPI/Swagger) Experience with cloud infrastructure: GCP, AWS, or Azure; containerisation with Docker/Kubernetes Familiarity with geospatial processing libraries (GDAL, Rasterio, Shapely, GeoPandas) is an advantage Agentic AI & LLM Systems Experience with agentic tool-serving frameworks (e.g. Model Context Protocol) or equivalent LLM tool-use infrastructure Experience building LLM-integrated applications: tool-use pipelines, agent orchestration, context management Familiarity with Claude API, OpenAI API, or equivalent LLM APIs for building AI-powered applications Ability to design robust, testable, well-scoped agent tools that function reliably as part of agentic workflows Frontend & Product Proficiency in modern frontend development: React, TypeScript, and associated tooling Ability to build clean, functional data dashboards and partner-facing interfaces Product instinct — comfort contributing to roadmap decisions, user experience trade-offs, and feature prioritisation Engineering Practices Git/GitHub: branching strategies, code review, CI/CD pipelines Testing: pytest, unit/integration/e2e strategies, test automation Technical documentation: architecture diagrams, API references, developer guides AI-assisted development — fluent use of LLM coding assistants to accelerate delivery Personal Attributes Ownership-Driven: Takes full ownership of systems — from architecture through to production reliability. Doesn’t leave problems for others. Full-Stack Breadth: Comfortable moving between backend data pipelines, API layers, frontend interfaces, and agentic AI systems without losing depth. Product-Minded: Thinks about who uses the system and why — not just how it’s built. Naturally contributes to product decisions. Collaborative: Works effectively with diverse technical partners (Kartoza, Predictia, TAHMO) and cross-functional colleagues (agromet scientists, program managers). Clear Communicator: Produces documentation and architecture summaries that non-engineers can understand. Comfortable presenting technical systems to partner and donor audiences. Adaptable & Curious: At ease in a fast-moving, mission-driven startup. Leans into new technologies — especially at the frontier of agentic AI. Preferred (Not Required) Experience with geospatial platforms, earth observation pipelines, or agricultural data systems Familiarity with Icechunk, Zarr v3, or other cloud-native array storage systems Working knowledge of weather or climate data formats and NWP/ML forecast products Experience building or integrating with SMS, IVR, USSD, or low-bandwidth delivery channels Prior exposure to the smallholder farmer advisory or climate services value chain in Africa Experience developing in African technology contexts A Typical Week This is a hands-on, deep-technical role with regular collaboration across internal teams and external partners. Time Allocation Activity ~40% Platform & Agentic Engineering Backend development, API work, agentic systems development, Zarr/Icechunk architecture, data pipeline work. Primarily Python, Django, and agentic framework tooling. ~25% Frontend & Product Development Dashboard and partner interface development (React/TypeScript), API documentation, developer tooling, feature scoping and UX input. ~20% Collaboration & External Engineering Joint architecture sessions, code reviews, sprint planning, and technical oversight of contracted deliverables with core external partners. ~15% Documentation, Testing & Platform Ops Writing technical documentation, system tests, monitoring production systems, internal knowledge sharing, and contributing to architecture records. Tools & Platforms Deep expertise in all tools is not expected at hire — willingness and ability to learn quickly is. Category Tools Core Platform Django/Python backend, PostGIS, GCP cloud infrastructure, Docker, GitHub Agentic & AI Agentic tool-serving frameworks (incl. MCP), Claude API, LLM tool-use pipelines, agent orchestration patterns Data & Geospatial Zarr, Icechunk, Xarray, NetCDF, GeoTIFF, GDAL, Rasterio, GeoPandas Forecast Products CBAM, GenCast, NexGen (Tomorrow.io), TAMSAT — ingested and served via GAP Frontend React, TypeScript, modern JS tooling, data visualization libraries Development Python, Git/GitHub, CI/CD, pytest, Jupyter, AI coding assistants Program Management GitHub Projects, Google Workspace, Slack Travel & Location Category Details Location Remote-first. Preference for candidates in East Africa or European time zones for coverage of collaboration. Travel Approximately 10–20%. Occasional technical missions to East Africa for partner workshops, platform demonstrations, and field visits. Travel to donor meetings or conferences as required. Working Hours Flexible. Must have overlap with East Africa (EAT, UTC+3) and periodic overlap with European time zones. Growth Path This role carries significant technical ownership from day one. Over time, the person in this position is expected to grow into broader technical leadership of TomorrowNow’s platform architecture — shaping the long-term GAP roadmap, leading the agentic intelligence strategy, and mentoring junior engineers as the team scales. As TomorrowNow expands its platform partnerships and advisory reach across Africa and beyond, this role is positioned to become a defining engineering leadership position within the organisation. Why Join TomorrowNow? Transform Lives at Scale: Help build the platform that will reach 100 million smallholder farmers with world-class agromet intelligence Build at the Frontier: Work at the intersection of agentic AI, geospatial systems, and agricultural technology — problems that few engineers in the world are solving Genuine Ownership: This is not a cog-in-a-machine role. You will shape what gets built, how it works, and where it goes next Collaborative Culture: Work alongside a passionate, talented team that combines deep science expertise with a startup’s bias for action and impact Entrepreneurial Environment: Join a mission-driven organisation where systems are evolving, initiative is valued, and your work directly shapes the product. What We Offer Competitive salary and benefits Remote work environment with flexible hours Opportunities for professional growth and development A high-performance, collaborative, and mission-driven work culture Our Culture We believe that magic happens when people work together. Your success is measured by your impact and deliveries — not by hours clocked. We believe in transparency to build trust, humility to listen, and agility to adapt quickly and effectively. We have audacious goals and always see people first. Each person has their own growth path — because the only way for TomorrowNow to grow is if you grow. How to Apply Interested candidates should apply via [JazzHR Link] and provide a résumé that clearly highlights: professional experience building and shipping production software systems (specify stack, scale, and role); examples of full-stack or platform work taken from architecture through to deployment; experience with agentic AI, LLM integrations, or AI tool-serving systems; and any exposure to geospatial, climate, or agricultural data contexts. Applications will be reviewed on a rolling basis. Shortlisted candidates will be contacted for the next steps. You will have the opportunity to make a major contribution to a transformative vision that will help the lives of millions of people in Africa. TomorrowNow — 100 Million Resilient Smallholder Farmers in Africa
This job posting was last updated on 3/10/2026