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Strong Tier-1 brand, metro locations, and broad high-visibility AI skill requirements increase applicant competition.
Specialized AI/ML infrastructure skills with financial compliance expectations moderately limit cross-industry transferability.
High: explicit 12+ years plus deep ML, LLM, MLOps, cloud, and security requirements.
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Design, develop, and deliver scalable, secure, and high-performance AI/ML software solutions including agentic AI systems and LLM applications.
Lead architectural decisions, mentor engineering teams, and drive adoption of AI technologies across multiple business units ensuring enterprise-grade reliability, security, and governance.
Advise senior leadership and cross-functional stakeholders, manage risks, and implement continuous improvements aligned with business strategies.
Bachelor's degree or above in Computer Science, Engineering, Mathematics, or related discipline.
Minimum 12 years of software engineering experience or experience designing scalable ML infrastructure, model serving platforms, and MLOps systems at enterprise scale.
Expert-level proficiency in Python (FastAPI, async patterns) and/or Go/Java with demonstrable production experience serving high-throughput, low-latency workloads.
Experience with AWS (EC2/EKS, S3, IAM, RDS, AI services), Docker, Kubernetes, distributed systems architecture, and secure coding practices.
Senior engineer capable of leading complex, multi-year AI/ML projects with a focus on agentic AI and LLM-scale deployments.
Experience advising leadership on AI technical strategy, risk management, and governance within regulated environments, preferably financial services.
Strong communicator skilled at influencing stakeholders and collaborating across cross-functional teams to integrate AI solutions aligned with enterprise goals.