Senior Engineer - Gen AI
Ahmedabad Full-time Senior AI Engineering
At a glance
Senior AI Engineering role at Ac (Ec). Ahmedabad · full-time.
Pay not stated AI Engineering salary
RoleAI Engineering
SenioritySenior
LocationAhmedabad
EmploymentFull-time
PostedDec 2, 2025 · 10mo ago
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Design, test and launch generative AI systems, including language models, for specific business uses
- Build multi-step AI agents and connect them to knowledge bases and outside data through retrieval systems
- Create data pipelines that prepare, index and retrieve text, tables, documents and images
- Tune prompts and models, assess results, run A/B tests and use findings to improve performance
- Test LLMs for vulnerabilities, then work with platform teams to deploy, monitor and scale them safely
What you bring
- Five to six years in software engineering or AI roles, including at least two to three years working directly with generative AI and LLMs
- Strong Python skills and experience with machine-learning libraries such as scikit-learn, TensorFlow or another listed library
- Hands-on work with LLMs, retrieval systems, vector databases and deployed agent workflows
- Experience using Garak or a comparable scanner to find and address weaknesses in AI systems
- Experience building content moderation systems, plus familiarity with cloud AI services and Docker or Kubernetes
Who this fits
This senior engineering role suits someone who has built production generative AI systems and can turn business needs into designs with measurable performance, cost and safety limits. The position is based in Ahmedabad, India, and is full time.
From the employer
Position:
Senior Engineer - Gen AIJob Description:
Job Profile Specification: Senior Generative AI / Agentic AI Engineer (5–6 years)s
Role summary:
- Senior-level engineer (5–6 years of professional experience) focused on designing, building, and deploying production-grade generative AI and agentic-AI solutions.
- Responsible for delivering secure, scalable, and business-oriented AI systems that operate on structured and unstructured data and enable AI-driven decision-making
Required experience
- 5–6 years of industry experience in software engineering and AI-related roles.
- Minimum 2-3 years of direct experience with Generative AI and Large Language Models (LLMs).
Key Responsibilities:
- Architect, develop, test, and deploy generative-AI solutions (online/offline LLMs, SLMs, TLMs) for domain-specific use cases.
- Design and implement agentic AI workflows and orchestration using frameworks such as LangGraph, Crew AI, or equivalent.
- Integrate enterprise knowledge bases and external data sources via vector databases and Retrieval-Augmented Generation (RAG).
- Build and productionize ingestion, preprocessing, indexing, and retrieval pipelines for structured and unstructured data (text, tables, documents, images).
- Implement fine-tuning, prompt engineering, evaluation metrics, A/B testing, and iterative model improvement cycles.
- Conduct/model red-teaming and vulnerability assessments of LLMs and chat systems using tools like Garak (Generative AI Red-teaming & Assessment Kit).
- Collaborate with MLOps/platform teams to containerize, monitor, version, and scale models (CI/CD, model registry, observability).
- Ensure model safety, bias mitigation, access controls, and data privacy compliance in deployed solutions.
- Translate business requirements into technical designs with clear performance, cost, and safety constraints.
Required Skills and Experience:
- Strong proficiency in Python and experience with ML/AI libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face ecosystem).
- Hands-on experience with LLMs, RAG, vector databases, and retrieval pipelines.
- Practical experience deploying agentic workflows and building multi-step, tool-enabled agents.
- Experience using Garak (or similar LLM red-teaming/vulnerability scanners) to identify model weaknesses and harden deployments.
- Demonstrated experience implementing content filtering / moderation systems.
- Solid skills working with structured and unstructured data and advanced feature engineering.
- Familiarity with cloud GenAI platforms and services (Azure AI Services preferred; AWS/GCP acceptable).
- Experience building APIs/microservices; containerization (Docker), orchestration (Kubernetes).
- Strong understanding of model evaluation, performance profiling, inference cost optimization, and observability.
- Good knowledge of security, data governance, and privacy best practices for AI systems.
Preferred / differentiating qualifications
- Hands-on fine-tuning experience and parameter-efficient tuning methods.
- Experience with multimodal models and retrieval-augmented multimodal pipelines.
- Prior work on agentic safety, tool-use constraints, LLM application firewalls, or human-in-the-loop systems.
- Familiarity with LangChain, LangGraph, Crew AI, or similar orchestration libraries.
Values & behaviours
- AI-first thinking: consistently seeks AI-enabled solutions to business problems.
- Data-driven mindset: makes decisions based on measurable insights and metrics.
- Collaboration & agility: effective contributor in cross-functional, fast-paced teams.
- Problem-solving orientation: looks beyond the obvious to unlock product and business value.
- Business impact focus: designs solutions with measurable outcomes and real adoption.
- Continuous learning: stays current with academic research, open-source tooling, and best practices.