AI Engineer at Sixtyfour (X25)

Sixtyfour builds AI research agents that discover, link, and reason over information about people and companies, automating research workflows for sales, recruiting, and marketing. This AI Engineer role involves designing and shipping agentic systems for reliable data fetching, extraction, and normalization across the web and APIs. Key responsibilities include owning robust web scraping, developing backend services in Python + FastAPI, scaling workloads on AWS + Docker, and integrating third-party APIs for enrichment and search.

Must Have

• Design and ship agentic systems with tool calling and structured outputs.
• Own robust web scraping, including CAPTCHA and anti-bot evasion.
• Develop backend services using Python and FastAPI.
• Scale workloads on AWS and Docker, managing autoscaling and fault tolerance.
• Parallelize external API requests safely with rate limits and retries.
• Integrate third-party APIs for data enrichment and search.
• Transform and analyze data using Pandas for normalization and QA.
• Experience with agentic architectures and prompt engineering.
• Proven expertise in web scraping techniques.
• Production experience with AWS and Docker services.
• Build high-throughput data/IO pipelines with concurrency and resilient retries.
• Integrate diverse external APIs, handling auth and pagination.
• Strong data wrangling skills with Pandas.
• Demonstrate excellent ownership, product sense, and pragmatic debugging.

Good to Have

• 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.

About Sixtyfour

We build AI research agents that can discover, link, and reason over everything about people and companies. The platform turns that intelligence into automated research workflows for sales, recruiting, and marketing.

About the role

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

• 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, 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.

Nice to have

• 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.

Technology

Language Models, Opensearch/Elasticsearch, Next.js (typescript), Python, FastAPI, AWS, Docker, Celery workers, Playwright, Supabase, Stripe