Key Responsibilities
AI Agent Development
- Build and deploy
AI-powered conversational agents
(voice + chat) for client-facing and internal workflows.
- Fine-tune and integrate
LLMs (OpenAI, Anthropic, Cohere, etc.)
into business workflows.
- Implement intent recognition, entity extraction, and dialogue management with frameworks like
Rasa, LangChain, or Haystack
.
Process Automation
- Automate workflows such as
lead intake, survey booking, billing, reminders, and consignment tracking
.
- Integrate AI agents with
CRM systems (HubSpot, Salesforce, Zoho)
and
billing tools (QuickBooks, Xero)
.
- Leverage
N8N, Replit, ,
Zapier
or custom APIs
for workflow orchestration.
System Architecture & Integrations
- Design modular architectures for scalable automation.
- Build API-first integrations with WhatsApp, email, SMS, and telephony platforms (Twilio, Vonage).
- Develop monitoring dashboards to track agent performance (response times, accuracy, conversion impact).
Optimization & Continuous Learning
- Apply
prompt engineering and fine-tuning
for domain-specific tasks (e.g., moving inquiries, insurance terms, shipment tracking).
- Use analytics to continuously improve agent performance (reduce errors, increase automation coverage).
- Implement
feedback loops
to retrain models on real-world conversations.
Required Technical Skills
- Strong proficiency in
Python or
(for automation scripting and AI integration).
- Experience with
AI agent frameworks
(LangChain, Rasa, AutoGPT, AgentGPT).
- Familiarity with
NLP/LLM APIs
(OpenAI GPT models, Hugging Face transformers, Cohere).
- Hands-on experience with
automation platforms
(Zapier, Make, Airflow) and API development.
- Knowledge of
cloud deployment
(AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Understanding of
databases & vector stores
(PostgreSQL, Pinecone, Weaviate, ChromaDB).
- Ability to integrate
voice AI
(e.g., Twilio, Deepgram, ElevenLabs) into real-time workflows.