AI Engineer

About Sixtyfour

Sixtyfour is a data orchestration engine for company and people data. Our AI agents specialize in enriching detailed data points about individuals and organizations, gathering information from both public and proprietary sources. We enable enterprise customers to build custom data pipelines that help them find, enrich, qualify, and act on company-specific requirements for people and business data.

Our Mission

To power how enterprises understand and act on people and companies with world-class intelligence.

• 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.

• Hands-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, Cloud Watch).
• 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
  , Open Telemetry, 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.