Tech Lead (TypeScript)

Tech Lead (TypeScript) Company Orcrist is building a next generation data intelligence platform using cutting-edge technologies. We're handling petabyte-scale data with sub-second queries. Our product (OIP) is a Kubernetes‑based platform delivered as B2B SaaS or as a self‑hosted/on‑prem solution, including air‑gapped deployments. Role Lead the team that builds ML‑powered enrichment and search/insight features across our software platform. Think entities and relationships, records browsing, labeling/graphs/profiles, and audio/chat/files (transcription, translation, OCR/NER, summarization, geocoding). You’ll stay hands‑on (ca. 50%), unify batch + streaming pipelines, define typed contracts between our TypeScript services and Python model services, and run inference with clear SLOs and cost controls across SaaS and on‑prem/air‑gapped environments. What you'll do Own and evolve Insights surfaces: Shaping APIs, data models, and UX of entity Insights, records browser, labeling/graph/profile, and audio/chat/file insights. Integrate ML the right way: Define typed, versioned contracts and rollout gates between TypeScript (Next.js/Node) and Python model services; use feature flags, canaries, and safe rollbacks. Raise search indexing quality: Manage OpenSearch schemas and analyzers, design reindex/backfill strategies, and run relevance experiments/A‑B tests. Build evaluation feedback loops: Create offline/online evaluation harnesses (precision/recall, F1, WER/CER, latency/cost SLOs) and integrate human‑in‑the‑loop corrections. Operate streaming + batch enrichment: Design idempotent, backpressure‑aware pipelines (Kafka/Temporal) that support both backfills and real‑time updates. Make it observable and reliable: Instrument traces/metrics/logs end‑to‑end; own SLOs/error budgets and incident response for the Insights surfaces. Manage cost/performance: Reduce inference spend via batching, caching, quantization choices, and right‑sizing GPU/CPU resources; publish and track budgets. Partner across teams: Work with Research on model selection/release, and with Foundation/Platform on data contracts, search/index hygiene, and deployment. Keep data safe: Ensure provenance, auditability, and compliant handling of PII/classified data across SaaS and air‑gapped installs. About You 7+ years software engineering with TypeScript/Node.js (full‑stack with React ). Deep Kubernetes experience operating production workloads. Cloud experience (GCP, AWS, Azure or similar). Led technical teams and major architecture migrations. Strong mentorship track record. Shipped ML‑powered product features (search, ASR/OCR/NER/translation/summarization) and know how to evaluate them (precision/recall, F1, WER/CER, latency/cost SLOs). Strong with ElasticSearch/OpenSearch : schemas, analyzers, reindexing, and relevance tuning. Built event‑driven systems and batch + streaming pipelines (e.g. Kafka, Flink) with an eye for idempotency and exactly‑once where it matters. Experience with observability: OpenTelemetry, Prometheus, Grafana, SLOs, and error budgets. Nice‑to‑haves Experience in B2B SaaS or government/defense contexts. Worked with on‑prem/air‑gapped deployments. Open‑source contributions, speaking/writing on technical topics. Python coding skills. What We Offer Modern architecture stack (TypeScript, React, Node.js, Kafka, PostgreSQL, Kubernetes, GCP). Remote‑first in Germany with occasional team events in Berlin. Home office budget and great equipment. 30 days vacation. Direct impact on critical missions across private and public‑sector customers. ... (truncated, view full listing at source)