Salesforce AI Integration Architect (Indore)

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;
- Strong 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 up-to-date technologies and global clients.

Data Engineer 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 Required Skill Profession Other General Apply on Kit Job: kitjob.in/job/4mr0ra