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Build and ship small end-to-end features across frontend and backend systems for research infrastructure. The role involves learning from experienced engineers, using AI coding tools, pair programming, collaborating with the team, and deploying production software. Candidates should have 0–3 years of experience, a strong computer science or related educational background, experience using AI coding assistants, and demonstrated work through GitHub repositories or side projects.

Lead design and implementation of backend services, APIs, data pipelines, and distributed systems. Own service lifecycles, CI/CD, container orchestration, observability, and infrastructure-as-code. Diagnose performance and reliability issues, mentor engineers, write ADRs and docs, and collaborate with Product and Design to deliver robust, scalable solutions.

Design, build, and operate AWS-based production platform; improve CI/CD, reliability, observability, incident response, cost efficiency, and guardrails for agent-involved workflows. Drive operational analytics, testing/rollback mechanisms, human-in-loop approvals, and compliance foundations.

Lead technical architecture and build a hands-on engineering organization, leveraging AI coding tools and cloud-native infrastructure. Hire and mentor engineers, set engineering standards, collaborate tightly with research and product, and deliver scalable, reliable systems for a global scientific community.

Lead product strategy and execution for Bond and new AI-first research tools. Translate MCP/LLM grounding, retrieval, and corpus ingestion architecture into customer-facing roadmaps and specs, work with engineering and GTM on enterprise and lab requirements, mitigate product risks, represent product in customer/design-partner conversations, and help build the product function.

Lead and set the research agenda, perform hands-on technical research on graph databases, recommender and large-scale ML systems, translate findings into engineering decisions, and mentor junior researchers while partnering cross-functionally to drive product impact.

Build demos, sample integrations, landing pages, and technical content to enable POCs and shorten time-to-value. Support sales/solutions engineering on evaluations and RFPs, instrument GTM metrics, prototype PLG mechanics, and represent Valency in developer communities while partnering with product and engineering on enablement.

Open application inviting candidates to propose a role at Valency. Send resume/bio, a short note describing your fit, and work samples. The small hybrid team builds AI-first research and knowledge infrastructure; successful candidates are systems thinkers comfortable with ambiguity who enjoy early-stage product work.