Solutions Architect
$160k - $225kAntares Capital
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. Responsibilities
- 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.
- 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.
- 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.
- Orchestration & Scheduling: BMC Control-M (job flows, calendars, APIs, event-driven triggers); awareness of complementary schedulers/orchestrators.
- Observability & AIOps: Datadog (metrics/logs/traces, RUM, synthetics, dashboards, alerts), OpenTelemetry concepts.
- DevOps & Platform: Git-based workflows; CI/CD (e.g., GitHub Actions/Azure DevOps/Jenkins); artifact management; IaC (e.g., Terraform); containers (Docker, Kubernetes); secrets and policy-as-code.
- 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.
- Systems Thinking & Architecture Rigor
- Operational Excellence
- Data-Driven Decision Making
- Stakeholder Influence
- Clear Communication
- Continuous Improvement & Learning
- Must have unrestricted authorization to work in the United States.
- Must be willing to comply with pre-employment screening, including but not limited to drug testing, reference verification, and background check.
- Role may be hybrid/onsite at an Antares office; occasional travel as necessary.
Vacancy posted 3 days ago
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