Role overview
Software Engineer — Agent Orchestration & Autonomous Research (AI × Finance)
Role Overview
Help build the intelligent backbone that powers autonomous AI research for institutional finance. As a Software Engineer , you’ll design the core orchestration layer that coordinates specialized agents, steers multi-step research workflows, and executes mission-critical analysis with reliability, observability, and security at scale.
Why This Role
- Foundation work: Ship the systems that enable agents to reason, collaborate, and deliver answers on real financial questions.
- High leverage: Your architecture decisions will shape how autonomous research is performed across multiple enterprises.
- Production impact: What you build will run against live data, under real SLAs, and support high-stakes decisions.
Your First 90 Days
- Design and launch a production multi-agent workflow with senior mentorship and clear success metrics.
- Stand up an agent-orchestration service (state machines, task queues, retries, circuit breakers) for a real research use case.
- Own a core subsystem end-to-end—from architecture and implementation to deployment and on-call.
- See your code power autonomous research for a top institutional client.
What You’ll Build
- Agent Orchestration & Workflow Engines: Coordination services that route work across specialized agents, enforce deadlines, and guarantee idempotent execution.
- Multi-Agent Architecture: Communication patterns, task delegation, result synthesis, and dynamic resource allocation across heterogeneous workloads.
- Autonomous Execution Frameworks: Long-running, multi-phase flows with automatic backoff, error recovery, and graceful degradation—while preserving human oversight.
- Model Integration & Routing: Interfaces for multiple LLM providers and domain models with fallback rules, A/B evaluation, and cost/latency budgets.
- Real-Time Data Pipelines: Event-driven ingestion for market data, filings, news, and alternative datasets that trigger agent workflows.
- Memory & Context: Vector search and knowledge graphs that maintain long-horizon context, reuse prior analysis, and improve retrieval quality.
- Enterprise-Grade Reliability: Authentication, authorization, audit logs, and compliance-ready telemetry fit for regulated customers.
What We’re Looking For (Must-Haves)
- 2+ years building production-scale distributed systems or backend services.
- Strong CS fundamentals: algorithms, concurrency, systems design, and debugging multi-service architectures.
- Experience with agent frameworks or multi-agent coordination patterns.
- Fluency in Python, Node.js, or Rust; comfortable with microservices and event-driven designs.
- Hands-on experience with vector databases and semantic retrieval (e.g., Pinecone, Weaviate, Chroma).
- Track record of shipping resilient systems that support real users and tight SLAs.
- Clear technical communication with both engineers and business stakeholders.
What we're looking for
- Background building AI/ML production systems, workflow orchestration, or autonomous agent platforms.
- Familiarity with financial data sources, APIs, or enterprise integrations.
- Experience with Kafka (or similar), Kubernetes, and infrastructure-as-code.
- Mentoring or technical leadership experience; setting architectural direction.
- Startup experience or substantial side projects built from scratch.
How We Work
- Ownership: Engineers own outcomes end-to-end—design, ship, measure, iterate.
- Evidence-driven: We prioritize telemetry, experimentation, and rigorous post-incident learning.
- Safety & Reliability: Guardrails, fallbacks, and observability are first-class citizens.
Mentorship & Growth
- Weekly 1:1s with senior engineers experienced in enterprise-scale distributed systems.
- Deep architectural reviews and guidance on multi-agent/agentic system design.
- A clear path toward technical leadership and ownership of critical subsystems.
- “Learn by shipping” culture—production systems powering real research.
Representative Tech Stack
- Backend: Python, Node.js, Rust; PostgreSQL, Redis
- AI/ML: Multiple LLM providers; embeddings; vector databases
- Infrastructure: AWS, Docker, Kubernetes, Temporal, Kafka, Airflow
- Observability: Metrics, logs, traces (e.g., Datadog or similar)
- Tooling: Git, GitHub Actions, Pulumi
Interested?
If you’re excited to architect the backbone of autonomous research—where AI, real-time data, and distributed systems meet—we’d love to connect.
About Andiamo Talent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world’s largest and most well-known companies.
For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.
Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com