AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation.
At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.
We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.
We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.
We are looking for a GenAI-focused software engineer to design, build, and maintain production-grade AI workflows on top of AHEAD’s existing platforms, SDKs, and guardrails. This role sits within our internal eTech Engineering organization, focused on using AI to improve the Product Development Lifecycle (PDLC), Software Development Lifecycle (SDLC), and internal business workflows.
You will partner closely with product, platform, and domain stakeholders (e.g., data, applications, operations) to translate real-world internal problems into reliable, scalable, and secure GenAI solutions that build on established tools and patterns rather than bespoke infrastructure.
GenAI Workflow & Service Development
Build and iterate on agentic and multi-step workflows using approved orchestration frameworks and platform patterns (e.g., LangGraph, AgentCore, LangChain).
Consume existing retrieval/RAG and search abstractions to improve response quality, grounding, and reliability, tuning parameters (top-k, scoring, filters) rather than re-implementing core retrieval infrastructure.
Develop robust tooling and APIs for agents, including clear input/output schemas, error contracts, versioning, and observability hooks.
Platform Integration & Governance
Operate within established platform, security, and governance guardrails (RBAC, data access boundaries, PII handling, logging, audit) instead of building custom, one-off mechanisms.
Leverage existing platform SDKs, templates, and patterns for configuration, deployment, and monitoring of GenAI workloads.
Work in a cloud-native AWS and Azure environments (e.g., cloud native applications, environment variables, secrets management, logging/metrics/tracing), collaborating with platform teams as needed rather than owning core infra design.
Partner with product managers, internal business stakeholders, and UX to translate problem statements and evaluation criteria into concrete, production-ready workflows.
Collaborate with data and application teams to integrate GenAI capabilities into existing systems (e.g., internal tools, portals, automation flows) with minimal disruption.
Participate in design reviews, code reviews, and architecture discussions, ensuring solutions are maintainable, observable, and aligned with platform standards.
Operations & Continuous Improvement
Own the operational health of GenAI workflows you build: monitoring, alerting, troubleshooting, and iterative improvement.
Incorporate evaluation and guardrail checks (e.g., automated tests, evaluation harnesses, red/blue team feedback) into workflows to improve quality and safety over time.
Act as a “high adopter of AI to build AI”, continuously using AI tools (e.g., Glean, Devin, Windsurf, Claude) to accelerate design, development, testing, and documentation.
Practical, hands-on exposure to LLM/GenAI integration (e.g., AWS Bedrock, Azure AI, OpenAI, Anthropic), including:
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.
Experience integrating GenAI into business workflows or engineering workflows (e.g., SDLC/PDLC automation, internal tools, support workflows, data/analytics workflows).
Familiarity with MLOps, data platforms, or observability tools used to track quality, performance, and usage of GenAI features.
Evidence of being an early and high adopter of AI tools for your own development workflow (e.g., using code assistants, AI debuggers, documentation generators, or experimentation tools as part of daily practice).
Why AHEAD:
Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between.
We fuel growth by stacking our office with top-notch technologies in a multi-million-dollar lab, by encouraging cross department training and development, sponsoring certifications and credentials for continued learning.
India Employment Benefits include:
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
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
