Senior Software Engineer Jobs

About The Position

Requirements

• BS or MS in Computer Science or a related technical field, or equivalent practical experience.
• At least 5 years of professional software engineering experience.
• Strong hands-on development experience in object-oriented languages such as Python, Java, or JavaScript/TypeScript.
• Hands-on experience building AI-enabled applications, intelligent workflows, or agentic systems using modern LLMs and AI development frameworks.
• Practical experience with AI engineering patterns such as agent orchestration, tool/function calling, retrieval-based systems, prompt and context engineering, structured outputs, evaluation, observability, or guardrails.
• Experience taking AI-enabled systems beyond prototypes toward production, including testing, monitoring, reliability, security, and operational considerations.
• Strong experience with cloud-native architectures, containerized microservices, APIs, and modern software delivery practices.
• Strong analytical, problem-solving, software design, and debugging skills.
• Commitment to engineering quality through automated testing, code reviews, observability, and continuous delivery.
• Ability to independently own complex technical problems and clearly communicate designs, decisions, and trade-offs.
• Product mindset, learning agility, and interest in keeping current with the evolving AI engineering landscape.

Nice To Haves

• Experience mentoring engineers or leading technical workstreams.
• Understanding of financial markets, asset management, or financial instruments.

Responsibilities

• Own end-to-end design and delivery of production-grade AI agents and intelligent systems, including architecture, implementation, testing, evaluation, deployment, observability, and production support.
• Design agentic workflows using orchestration, tool integration, retrieval-based systems, structured outputs, context management, and appropriate human-in-the-loop patterns.
• Partner with product owners and business stakeholders to understand priorities, shape solution direction, evaluate approaches, and translate complex needs into scalable AI solutions and measurable outcomes.
• Lead technical workstreams from rapid experimentation and validation through production adoption.
• Establish evaluation and testing approaches for non-deterministic AI systems, including quality metrics, regression testing, failure analysis, and production monitoring.
• Make informed engineering trade-offs involving models, prompts, context, tools, latency, cost, reliability, security, and maintainability.
• Contribute reusable AI capabilities and shared engineering patterns that improve speed, quality, and consistency across teams.
• Lead code and design reviews, mentor less-experienced engineers, and help colleagues solve complex technical problems.
• Own technical debt and continuously improve system quality, reliability, and maintainability.
• Evaluate emerging AI technologies and determine how they can deliver meaningful business value.
• Support the Build-Operate-Transfer model by preparing successful AI solutions for long-term ownership and scale by business-aligned technology teams.
• Clearly communicate technical designs, decisions, and trade-offs while balancing innovation, business value, scalability, risk, fiscal responsibility, and maintainability.

Benefits

• Competitive compensation.
• Annual bonus eligibility; discretionary bonus is determined based on company and individual performance.
• Generous retirement plan.
• Hybrid work schedule.
• Health and wellness benefits, including online therapy.
• Paid time off for vacation, illness, medical appointments, and volunteering days.
• Family care resources, including fertility and adoption benefits.