AI Engineer (Agentic / Gen AI)

Focus areas : Edge AI, Agentic AI

Location: Chennai, Tamil Nadu

Job Summary:

You'll lead applied research in creating and optimizing small language models (SLMs) and derived models

for range of use cases cutting across both structured and unstructured data - for edge AI deployment,

powering agentic systems, digital threads, and highly contextual knowledge graphs. Focus on real-world

EPC/manufacturing scenarios like autonomous workflow orchestration, connected operations, and aimed

at taking digital transformation in these sectors to the next generation of technologies and with

breakthrough impact.

Key Responsibilities:

• Design, train, and distill SLMs or derived models (e.g., from Llama/Mistral) for domain-specific

tasks in EPC/manufacturing, with deeper context engineering and mature agentic AI workflows,

optimizing for low-latency inference on edge devices for site level intelligence and predictability.

• Architect agentic AI frameworks that leverage SLMs for autonomous decision-making, such as

multi-agent orchestration for construction sequencing or factory floor optimization.

• Build and integrate digital threads-end-to-end data pipelines linking design, procurement,

construction, and operations-using SLMs for natural language querying and automation.

• Develop complex knowledge graphs to model intricate relationships in EPC ecosystems (e.g., asset

hierarchies, supplier networks, regulatory compliance), enhanced by SLM-driven reasoning and

graph RAG.

• Deploy edge AI solutions for real-time applications, including IoT sensor fusion, on-device anomaly

detection, and federated learning in harsh manufacturing environments.

• Prototype and benchmark systems for scalability, collaborating on MLOps pipelines with tools like

Kubernetes, TensorRT, and ONNX for edge-cloud hybrid deployments.

• Conduct research on SLM fine-tuning, quantization, and agentic behaviors, documenting findings for

internal adoption or publications.

Sensitivity: LNT Construction Internal Use

Required Qualifications:

• Master's or PhD in AI/ML, Computer Science, or related field (or equivalent experience).
• 4+ years in applied AI, with deep hands-on experience building/training SLMs or derived models

(e.g., LoRA/PEFT fine-tuning, model distillation).

• Proven expertise in edge AI deployment (e.g., NVIDIA Jetson, ARM-based inference, quantization

techniques like AWQ/GPTQ).

• Strong experience with agentic AI (e.g., LangChain, AutoGen) and Neo4j for complex knowledge

graphs (Cypher queries, graph embeddings, graph algorithms).

• Familiarity with digital threads in manufacturing/EPC: PLM integration, BIM data flows, or IIoT

protocols.

• Proficiency in PyTorch, Hugging Face Transformers, Neo4j, and edge frameworks (e.g., TensorFlow

Lite, OpenVINO).

Preferred Skills:

• Experience in EPC/manufacturing domains: procurement-to-pay automation, digital twins, or

supply chain graph analytics.

• Knowledge of federated learning, secure multi-party computation, or quantum-safe edge crypto.
• Contributions to open-source SLM/edge AI projects or relevant publications (e.g., ICML, NeurIPS

workshops).

Sensitivity: LNT Construction Internal Use