Salesforce AI Integration Architect (Indore)

Job Description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a Salesforce AI Integration Architect to design and build enterprise integrations between internal AI platforms and Salesforce Agentforce environments, scaling autonomous AI workflows across distributed systems. You will architect multi-step agentic AI orchestration patterns, define integration strategies using REST APIs, gRPC, and event-driven architectures, and establish security and governance guardrails for AI-native enterprise systems. The role requires deep expertise in Salesforce customization, LLM orchestration, and scalable distributed system design.

WHAT YOU WILL DO


- Architect end-to-end integrations between internal AI platforms, enterprise data systems, and Salesforce Agentforce environments;

- Design scalable, secure, and resilient distributed system architectures supporting autonomous AI workflows;

- Define integration strategies leveraging REST APIs, gRPC, event-driven architectures, and Salesforce-native capabilities;

- Design and optimize modular agentic AI systems through specialized micro-agent delegation;

- Build orchestration patterns for multi-step AI workflows, autonomous routing systems, and semantic tool execution;

- Apply best practices around prompt engineering, context management, token conservation, and LLM orchestration;

- Develop and enhance integrations using Salesforce Flows, Invocable Apex methods, APIs, connectors, and custom prompt templates;

- Enable complex backend processes to be exposed as intelligent agentic tools within Salesforce ecosystems;

- Collaborate with cross-functional teams to maintain unified API contracts and semantic consistency across enterprise systems;

- Author architectural decision records documenting technical trade-offs, constraints, and high-level requirements;

- Evaluate and select integration patterns including traditional APIs, Model Context Protocol, and Agent-to-Agent communication models;

- Balance performance, latency, scalability, reasoning overhead, and data sensitivity considerations in architectural decisions;

- Establish authentication boundaries, trust layers, and governance guardrails for AI-enabled enterprise systems;

- Ensure compliance with enterprise security standards, data governance policies, and secure data exposure practices;

- Partner with security and platform teams to maintain reliable and trustworthy autonomous agent execution.

MUST HAVES


- 6+ years of experience designing enterprise integrations and distributed system architectures ;

- Hands-on experience integrating systems with Salesforce ;

- Deep expertise with Apex methods , advanced Salesforce Flows , custom prompt templates, and Salesforce APIs and connectors;

- Strong experience with REST APIs , gRPC , event-driven architectures , and enterprise synchronization patterns;

- Solid understanding of AI and LLM concepts including prompt engineering , context management , token optimization , multi-step AI workflows , agent orchestration , and semantic routing systems;

- Experience designing scalable and secure distributed systems;

- Solid understanding of authentication, security, trust boundaries, and data governance;

- Experience documenting architecture decisions, trade-offs, and technical strategy;

- Excellent collaboration and communication skills across engineering, platform, data, and security organizations;

- Upper-intermediate English level.

NICE TO HAVES


- Experience with Model Context Protocol (MCP) ;

- Experience with Agent-to-Agent (A2A) integrations;

- Experience with MuleSoft or enterprise middleware platforms;

- Familiarity with Salesforce Agentforce ;

- Experience building or managing autonomous AI agents or micro-agent ecosystems;

- Experience with semantic tool discovery or AI-native integrations;

- Knowledge of Salesforce Bulk APIs and Salesforce Connect ;

- Experience operating within large-scale enterprise AI environments.

PERKS AND BENEFITS


- Remote work & local connection : Work where you feel most productive and connect with your team in periodic meet-ups.

- Legal presence in India : Full local compliance and structured work environment.

- Competitive compensation in INR : Dedicated budgets for growth, education, and wellness.

- Innovative projects : Work with modern technologies and global clients.

Requirements

6-8 years of experience in data engineering Proficient in Python programming — data pipeline development, transformation logic, and automation scripts Proficient in data query and analysis using SQL, with strong hands-on experience in BigQuery — partitioning, clustering, materialised views, and time-series query patterns at scale Hands-on experience building and scheduling pipelines using Cloud Composer (Apache Airflow) — DAG authoring, SLA alerting, retry logic, and dependency management Working knowledge of Dataproc (Apache Spark) — batch ingestion, Delta Lake merge operations, and incremental data processing Proficient in AI-assisted development tools such as GitHub Copilot, Cursor, or others for accelerating code generation and enhancing developer productivity Code versioning and collaboration using Git — branching strategies, pull request workflows, and pipeline-as-code practices Familiarity with REST APIs — consuming external data vendor APIs and building service-layer integrations Familiarity with GCP cloud technologies — Cloud Storage, Pub/Sub, Datastream, Cloud Monitoring, IAM, and VPC Service Controls Apply on Kit Job: kitjob.in/job/4mw14a