GenAI Engineer

📋 Description

• Design, implement, and sustain Python-based services and workflows that merge LLMs and GenAI capabilities with internal platforms and applications.

• Create and refine agentic and multi-step workflows utilizing approved orchestration frameworks and platform patterns (e.g., LangGraph, AgentCore, LangChain).

• Utilize existing retrieval/RAG and search abstractions to enhance response quality, grounding, and reliability, adjusting parameters (top-k, scoring, filters) instead of re-creating core retrieval infrastructure.

• Develop resilient tooling and APIs for agents, including clear input/output schemas, error contracts, versioning, and observability hooks.

• Implement structured output handling (e.g., JSON schemas, tool calls) to guarantee predictable behavior and facilitate easier downstream integration.

• Operate within defined platform, security, and governance guardrails (RBAC, data access boundaries, PII handling, logging, audit) rather than creating custom, one-off mechanisms.

• Leverage existing platform SDKs, templates, and patterns for the configuration, deployment, and monitoring of GenAI workloads.

• Work within cloud-native AWS and Azure environments (e.g., cloud native applications, environment variables, secrets management, logging/metrics/tracing), collaborating with platform teams as necessary instead of owning core infrastructure design.

• Collaborate with product managers, internal business stakeholders, and UX to convert problem statements and evaluation criteria into concrete, production-ready workflows.

• Partner with data and application teams to integrate GenAI capabilities into existing systems (e.g., internal tools, portals, automation flows) with minimal disruption.

• Engage in design reviews, code reviews, and architecture discussions, ensuring solutions are maintainable, observable, and align with platform standards.

• Contribute to internal enablement (playbooks, examples, patterns) to assist eTech Engineering and other teams in effectively utilizing GenAI capabilities.

• Manage the operational health of GenAI workflows you create: monitoring, alerting, troubleshooting, and iterative improvement.

• Integrate evaluation and guardrail checks (e.g., automated tests, evaluation harnesses, red/blue team feedback) into workflows to enhance quality and safety over time.

• Function as a “high adopter of AI to build AI,” consistently utilizing AI tools (e.g., Glean, Devin, Windsurf, Claude) to expedite design, development, testing, and documentation.

⛳️ Requirements

• 3–7 years of software engineering experience with substantial hands-on development in Python for production services and workflows.

• Practical, hands-on experience with LLM/GenAI integration (e.g., AWS Bedrock, Azure AI, OpenAI, Anthropic), including:

• Prompt and system design for reliability and control.

• Managing structured outputs (JSON schemas, tool calls, function calling).

• Experience in implementing agentic or multi-step workflows using orchestration frameworks such as LangGraph, AgentCore, or LangChain.

• Demonstrated ability to create clear tool APIs for agents with well-defined input/output schemas, error handling contracts, and versioning strategies.

• Experience in a cloud-native AWS/Azure environment, including:

• Lambda or similar serverless patterns.

• Environment configuration and secrets management.

• Logging, metrics, and basic observability/debugging.

• Familiarity with RAG/retrieval patterns as a consumer, including:

• Utilizing existing vector/search abstractions.

• Tuning retrieval parameters (top-k, similarity thresholds, filters).

• Understanding trade-offs in chunking, metadata enrichment, and indexing strategies.

• Strong software engineering fundamentals: version control (Git), testing, code review, CI/CD-friendly patterns, and clean code practices.

• Effective collaboration and communication skills, with the ability to work closely with product, UX, and domain experts to converge on pragmatic, production-ready solutions.

🏝️ Benefits

• Comprehensive health insurance coverage for employees, with options to extend coverage to dependents.

• Paid time off and company holidays, along with additional leave benefits as per policy.

• Flexible work arrangements, supporting work-life balance.

• Learning and development opportunities to support continuous growth and upskilling.

• Employee wellness initiatives and programs focused on physical and mental well-being.

• Retirement and statutory benefits in line with India regulations.

• Inclusive and people-first culture, with a strong focus on collaboration and ownership.