AI Engineer
SixtyfourSan Francisco, CA, United States5 days ago
Job type
- Full-time
Job descriptionHands‑on experience with agentic architectures (tool calling, structured outputs / JSON, planning / execution loops) and prompt engineering. Proven web scraping expertise : solving CAPTCHAs, session / auth flows, proxy rotation, stealth techniques, and legal / ethical constraints. AWS + Docker in production (at least two of : ECS / EKS, Lambda, SQS / SNS, Batch, Step Functions, CloudWatch). Building high-throughput data / IO pipelines with concurrency (asyncio / multiprocessing), resilient retries, and rate‑limit aware scheduling. Integrating diverse external APIs (auth patterns, pagination, webhooks); designing stable interfaces and backfills. Strong data wrangling with Pandas or equivalent; comfort with large CSV / Parquet workflows and memory / perf tuning. Excellent ownership, product sense, and pragmatic debugging. Entity resolution / record linkage at scale (probabilistic matching, blocking, deduping). Experience with Langfuse , OpenTelemetry, or similar for tracing / evals; task queues (Celery / RQ), Redis, Postgres. Search relevance (BM25 / vector / hybrid), embeddings, and retrieval pipelines. Playwright / Selenium, stealth browsers, anti-bot frameworks, CAPTCHA providers. CI / CD, infrastructure as code (Terraform), and cost / perf observability. Security & compliance basics for data handling and PII.
What you’ll do
- Design and ship agentic systems (tool calling, multi-agent workflows, structured outputs) that reliably fetch, extract, and normalize data across the web and APIs.
- Own robust web scraping : directory crawling, CAPTCHA handling, headless browsers, rotating proxies, anti-bot evasion, and backoff / retry policies.
- Develop backend services in Python + FastAPI with clean contracts and strong observability.
- Scale workloads on AWS + Docker (batch / queue workers, autoscaling, fault tolerance, cost control).
- Parallelize external API requests safely (rate limits, idempotency, circuit breakers, retries, dedupe).
- Integrate third-party APIs for enrichment and search; model and cache responses; manage schema evolution.
- Transform and analyze data using Pandas (or similar) for normalization, QA, and reporting.
- Pitch in across the stack : billing (Stripe), and occasional front-end changes to ship end-to-end features.
Minimum requirements
Nice to have
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Ai Engineer • San Francisco, CA, United States
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