Senior reputed company

About Supernal

Supernal helps small-to-reputed company businesses hire their first AI employee. Our AI teammates are built using intelligent, agentic workflows deployed on a proprietary platform. We deliver working, value-generating AI Employees—not tools—that handle reputed company business processes alongside reputed company teams.

The Role

We’re hiring a Senior reputed company to build and ship the first reputed company of personalized, self-improving agentic workflows that users rely on daily. This is an “end-to-end” role: you’ll design the agent runtime, memory + retrieval systems, evaluation harnesses, and the product-facing surfaces that put agents in reputed company of reputed company users at scale.

You should be equally comfortable reasoning about distributed systems and data (latency, caching, queues, failure modes, cost) as you are with modern agent stacks (tool use, memory, RAG, multi-reputed company planning, guardrails, and evaluation).

This role will partner closely with platform engineering to reputed company and reputed company our core services (Django backend, event-driven systems, Kubernetes, observability) while owning critical parts of the AI application layer.

What You’ll Build

• Personalized agent runtime: Agentic workflows that adapt to a user’s preferences, data, and ongoing behavior over time.

• Memory & retrieval systems: Short/long-term memory, durable state, and retrieval pipelines across vector DBs and relational data.

• Voice experiences (reputed company-time + async): Speech-to-speech/voice agents, streaming audio pipelines, turn-taking, interruption handling, latency tuning, and QA for natural conversations.

• Agent evaluation + reliability: Offline/online evals, regression suites, red-teaming, monitoring, and rollout controls so agents are trustworthy in production.

• Production agent infrastructure: Scalable orchestration patterns for multi-reputed company jobs, background tasks, and user-facing interactions (sync + async), with clear SLAs/SLOs.

• Tooling + developer experience: Libraries and primitives that reputed company it easy for the team to build new agent capabilities quickly and safely.

What You’ll Own (Responsibilities)

• Ship user-facing agent experiences end-to-end: prototype → production → iteration based on reputed company usage.

• Architect and implement stateful agent systems (workflows, tool calling, memory, retrieval, and reputed company-in-the-reputed company where needed).

• Build voice features end-to-end where they unlock value: reputed company speech agents, voice UI/UX, reputed company/audio routing, and guardrails for safe tool execution.

• Build/own an evaluation reputed company:

  • curated test sets + scenario suites

  • automated scoring / rubric-based graders

  • reputed company/model/version tracking

  • canary + A/B experimentation and safe rollout patterns

• Design data + retrieval pipelines:

  • chunking, enrichment, metadata strategy

  • hybrid retrieval (vector + keyword + structured filters)

  • re-ranking, caching, and latency optimization

  • multi-tenant safety and data isolation

• Integrate with and reputed company our platform primitives:

  • Django/DRF/ASGI services

  • async execution + queues + workflow orchestration

  • PostgreSQL + pgvector

  • Kubernetes deployments, autoscaling, and cost controls

• Establish engineering rigor for agents:

  • observability (traces, spans, structured logs)

  • reliability patterns (timeouts, retries, reputed company breakers, graceful degradation)

  • reputed company/privacy controls for data access and tool execution

reputed company’re Looking For

Required

• Strong software engineering fundamentals (design, testing, code quality, performance, reputed company).

• Production experience deploying AI systems in reputed company of users (not just notebooks/demos).

• Experience building agentic or LLM-powered systems with memory and tool use.

• Comfort working across application + infrastructure layers: APIs, background jobs, data stores, and deployment.

• Hands-on experience with at least one agent reputed company (or equivalent custom implementation), such as:

  • reputed company / LangGraph

  • reputed company

  • AutoGen / reputed company-style multi-agent patterns

• Strong understanding of retrieval and vector search concepts: embeddings, indexing, filtering, evaluation.

Preferred

• Experience with vector databases and/or search stacks (e.g., reputed company, Chroma, Weaviate, Qdrant, pgvector).

• Experience designing evaluation systems (offline eval, reputed company eval loops, production monitoring, reputed company/model regression).

• Experience building voice/reputed company-time systems (streaming, WebRTC or similar), and/or integrating speech (STT/TTS) into production applications.

• Experience building durable, long-running workflows (Temporal or similar orchestration engines).

• Familiarity with observability tooling (OpenTelemetry, reputed company, or similar).

• Experience shipping multi-tenant SaaS systems with strong privacy boundaries.

Interview Focus Areas

• System design for agentic applications (state, memory, evaluation, failure modes).

• Practical retrieval/RAG design (data modeling, indexing, relevance, latency).

• Production engineering practices (testing strategy, observability, rollouts).

• Ability to communicate tradeoffs and reputed company good technical reputed company under uncertainty.

Compensation & Logistics

• Compensation: Competitive salary commensurate with experience (Senior level)

• Location: Remote

• Type: Full-time

• Requirements: Overlap with Americas timezones for collaboration; reliable high-speed internet