Artificial Intelligence Engineer

Role: AI & Data Automation Engineer

Job Type: Full Time

Job Location: Hyderabad

Work Mode: Work from Office

Shift Timings: 10 AM to 7 PM IST

Job Responsibilities:

● Team Leadership and Autonomy: Lead and mentor a team of engineers, driving

architectural choices, establishing engineering best practices, and executing

milestones independently under minimal supervision.

● Complex Data Extraction and Parsing: Design and optimize data ingestion routines

for highly complex data, managing seamless extraction, transformation, and

normalization from PDFs (including OCR/unstructured text), CSV, JSON, and

complex databases.

● Intelligent Data Pipelines: Architect, build, and maintain robust end-to-end data

pipelines and ETL/ELT workflows tailored for AI systems, ensuring structural

integrity, strong data schema validation, and optimized throughput.

● Agentic Architecture Design: Architect and scale distributed, multi-agent systems

using the Agent-to-Agent (A2A) protocol to manage cross-platform orchestration,

decentralized task routing, and autonomous agent collaboration.

● Cognitive Modeling & Sequential Learning: Build, optimize, and maintain custom

sequence-to-sequence networks, time-series, and text prediction models utilizing

LSTM (Long Short-Term Memory) networks and specialized deep learning

architectures.

● Knowledge Infrastructure and Ontologies: Design and implement robust enterprise

knowledge bases, developing complex ontologies, semantic data models, and

knowledge graphs to enforce deterministic reasoning and domain-specific rules

within AI agents.

● Hybrid Retrieval (RAG) Pipelines: Develop and maintain hybrid Retrieval-

Augmented Generation (RAG) systems that balance on-premise data security

constraints with scalable, advanced cloud-based RAG models and vector databases.

● On-Premise & Cloud Deployment: Lead the deployment of foundational models

and agent runtimes on on-premise infrastructure (handling bare-metal or private

cloud security constraints) as well as continuous delivery to major cloud platforms

(AWS, GCP, or Azure).

● Core Software Engineering: Write production-grade, highly optimized, and clean

code exclusively in Python, implementing asynchronous patterns and robust API

integrations.

Requirements & Qualifications

● Experienced Leadership: 7+ years of hands-on experience in software or data

engineering, with a proven track record of leading technical teams and driving

projects forward autonomously.

● Data Mastery: Exceptional understanding of data structures and a strong

background in handling complex data variety, including structured and

unstructured data parsing (PDFs, CSV, JSON).

● Data Pipeline Expertise: Deep, hands-on experience designing scalable data

pipelines (using orchestration tools like Apache Airflow, Prefect, or Mage) to feed

large-scale AI applications.

● Core Language: Expert-level mastery of Python and its scientific/AI ecosystem

(PyTorch, TensorFlow, NumPy, Pandas).

● Deep Learning and NLP: Solid theoretical and practical understanding of recurrent

neural networks, specifically LSTMs, alongside transformers, text embeddings, and

tokenization strategies.

● Data and Knowledge Engineering: Proven track record in graph databases (e.g.,

Neo4j), RDF frameworks, ontology editing tools, semantic indexing, and high-

concurrency vector databases (e.g., Pinecone, Milvus, Qdrant, Chroma).

● Infrastructure Capabilities: Strong background in orchestration and virtualization

tooling (Docker, Kubernetes), private server configuration, and deploying models

within strict containerized, on-premise hardware environments.

● Cloud AI Ecosystems: Hands-on experience with managed cloud-native AI

platforms and APIs (e.g., OpenAI API, Anthropic Claude, AWS Bedrock, Google

• Vertex AI).