Platform & ecosystem thinking: Ensure solutions integrate coherently across identity, networking, security, data platforms, observability, and FinOps; anticipate scalability, cost, and resilience needs.
Architecture design & documentation: Produce enterprise-quality solution designs and diagrams (context, C4, sequence, data-flow), reference architectures, decision records, and non-functional requirements.
Application operations: Set operational and support patterns for applications across ecosystem, enabling L1/L2 support teams to oversee production systems.
Modernize Event Based Orchestration: Own the roadmap to rationalize, refactor, and migrate legacy schedules to scalable orchestrations in Control-M; establish release gates, run-book automation, and failure-auto-recovery patterns.
Observability & reliability: Design end-to-end telemetry using Datadog (metrics, logs, traces, RUM, synthetics), SLOs/SLA error budgets, and run-time guardrails; drive incident response patterns and post-incident learning.
DevOps leadership: Define and evangelize CI/CD standards (branching, pipelines, artifact strategy, environment promotion), infrastructure-as-code, secrets management, and policy-as-code for app, data, and ML workloads.
Enterprise LLM enablement: Provide baseline architecture for secure LLM deployments (model selection, RAG/vector stores, prompt management, guardrails, content filtering, monitoring), and partner with data, security, and legal/compliance on safe use.
Coaching & influence: Provide informal leadership-mentoring engineers and analysts; facilitating design reviews; aligning teams on standards without formal line management.
Vendor & stakeholder management: Evaluate tooling, manage POCs, and collaborate with partners to close gaps in performance, supportability, and compliance.
Requirements
Required:
10+ years of experience in solution/enterprise/software architecture across data and application domains, with a track record of designing and drawing enterprise-grade solutions.
Demonstrated expertise modernizing batch processing and DevOps workflows, including orchestration, release management, and production operations.
Hands-on proficiency operating observability platforms (preferably Datadog) and implementing metrics/logs/traces, SLOs, and incident management practices.
Solid understanding of LLM solution patterns (RAG, vector stores, guardrails, prompt patterns) and the organizational controls needed for enterprise adoption.
Strong data management foundation: data modeling, lineage, quality management, cataloging, access controls, and governance.
Proven ability to influence without authority and align diverse stakeholders on standards and best practices.
Excellent communication skills with the ability to translate complex technical concepts for non-technical audiences.
Preferred:
Experience with BMC Control-M at scale (migration, modernization, APIs, integrations).
Experience building/operating apps with React front-ends and Python/R back-ends; comfort with common frameworks and testing practices.
Prior exposure to responsible-AI frameworks (safety, privacy, model governance, auditability).
Financial services or asset-management domain experience.
Applications: React; Python (FastAPI/Django/Flask); R (Shiny/Plumber) or equivalents; REST/gRPC; eventing and messaging; API management.
Data: SQL and data modeling; ETL/ELT patterns; data quality and lineage; cataloging and governance; privacy and access management.
LLM/AI Basics: Model and endpoint selection, RAG architectures, vector databases, prompt and template management, evaluation and monitoring, guardrails/safety, responsible-AI controls.
Core Competencies
Systems Thinking & Architecture Rigor
Operatio
Additional Information
Job Description
The Solutions Architect role will lead the modernization and expansion of the firm's technology platform, working with product, engineering, security, and compliance teams to deliver high‑quality, scalable enterprise solutions. The role provides technical leadership to application development teams, establishing standards for API integration, event‑based architecture, batch orchestration, and observability. Key technologies include Node.js, JavaScript, Python, Kafka, Control‑M, and Datadog. The architect will also drive the evolution of software delivery practices through DevOps, CI/CD automation and automated testing, leading the way for AI‑assisted development using LLMs and generative AI across the software development lifecycle.
Antares Capital · Chicago