Lead Engineer, Full Stack Platform Engineer
TALENT Software Services
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Job summary
TALENT Software Services is seeking a senior engineer to drive end-to-end solution ownership across data generation, analytics, APIs, and user-facing experiences. You will shape requirements with product, architecture, and engineering teams and lead speed-focused design reviews.
You will champion cloud-native platforms, performance engineering, and AI-driven development, mentoring colleagues while delivering scalable, reliable software across domains.
Qualifications
- 7+ years of experience building scalable cloud-native systems.
- Experience with performance engineering, profiling, and optimization.
- Backend tech including Node.js (TypeScript) and Python.
- Frontend experience with React/TypeScript for data-intensive UIs.
- Designing and operating data pipelines and platforms (real-time and batch).
- Experience with AI/ML systems in production and model integration.
- Familiarity with LLMs, agent frameworks, or AI orchestration tools.
Responsibilities
- Own delivery of complex end-to-end engineering solutions—from data generation through analytics, APIs, and front-end experiences.
- Lead design of scalable cloud-native data and application platforms.
- Architect data generation systems to support testing, analytics, and AI model development.
- Integrate AI-driven components into production systems with responsible deployment.
- Drive architecture decisions, mentor engineers, and promote engineering excellence.
- Lead performance engineering, observability, and capacity planning.
Skills
Tools
Job description
Own delivery of complex, end-to-end engineering solutions—from data generation and ingestion through analytics, APIs, and user-facing experiences
Own delivery of complex, end-to-end engineering solutions—from data generation and ingestion through analytics, APIs, and user-facing experiences
Develop a deep understanding of business workflows, especially high-scale exam and operational systems
Partner with product, architecture, and engineering teams to shape requirements, define scope, and provide accurate level-of-effort estimates
Drive sprint planning, technical design discussions, and code/design reviews with a focus on speed, quality, and scalability
Lead design and implementation of scalable, high-performance, cloud-native data and application platforms
Architect data generation systems (synthetic, event-based, telemetry-driven) to support testing, analytics, and AI model development
Engineer high-performance systems, focusing on latency, throughput, resiliency, and cost efficiency
Implement robust observability, telemetry, and performance monitoring across all layers
Establish and enforce standards for automation, reliability, and performance engineering
Integrate AI-driven components (prediction, anomaly detection, intelligent insights) into production systems
Design and build agentic AI systems that can autonomously reason, plan, and execute tasks across engineering workflows
Leverage LLMs and orchestration frameworks to enable intelligent automation in data pipelines, testing, and operations
Incorporate AI-assisted development practices, including code generation, code review augmentation, and developer productivity tooling
Evaluate and implement AI-native architectures, including tool-using agents, multi-agent systems
Ensure responsible, secure, and scalable deployment of AI capabilities in production environments
Act as a senior technical leader driving architectural decisions and solving complex system challenges
Mentor engineers across backend, data, performance, and AI domains
Champion engineering best practices in performance optimization, scalability, security, and reliability
Clearly communicate technical strategy, tradeoffs, and decisions to stakeholders
Lead performance engineering efforts, including load testing, capacity planning, and system tuning
Build frameworks for data-driven performance benchmarking and optimization
Ensure systems meet strict SLAs for availability, latency, and scalability
Proactively identify risks and ensure readiness for high-stakes operational events
You have:
- 7+ years of experience building and operating scalable, distributed, cloud-native systems, including data platforms and APIs
- Strong experience with end-to-end system design, from data generation to front-end delivery
- Proven expertise in performance engineering, including profiling, load testing, and system optimization
- Hands-on experience with backend technologies such as Node.js (TypeScript preferred) and Python, building APIs and event-driven systems
- Strong experience designing and operating data pipelines and data platforms (real-time and batch)
- Experience building modern front-end applications (React/TypeScript) for data-intensive interfaces
- Deep knowledge of AWS services (Lambda, S3, Step Functions, SNS/SQS, Redshift, Athena, DynamoDB, etc.)
- Experience with Infrastructure as Code (CDK, Terraform, CloudFormation)
- Strong understanding of event-driven architectures, streaming, and telemetry systems
- Experience implementing observability and monitoring solutions (e.g., Grafana or similar)
- Experience with AI/ML systems in production, including model integration and operationalization
- Experience working with LLMs, agent frameworks, or AI orchestration tools
- Familiarity with agentic workflows, autonomous system
- Hands-on experience with AI-assisted coding tools (e.g., GitHub Copilot, ChatGPT, or similar) and integrating them into development workflows
- Understanding of RAG architectures, prompt engineering, and tool-augmented AI systems
- Familiarity with cell-based or multi-tenant architectures
- Experience designing systems for data isolation, security, and performance segmentation
- Exposure to synthetic data generation or simulation systems
- Experience with multi-agent AI systems or advanced automation pipelines
- Strong ownership mindset with the ability to drive end-to-end delivery
- Deep focus on performance, scalability, and reliability
- Curiosity and hands-on engagement with emerging AI technologies
- Ability to operate effectively in a fast-moving, contract-based environment
- Clear communication and strong collaboration across technical and non-technical stakeholders
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